918 results about "Test battery" patented technology

A method of repairing a used battery pack from an electric vehicle include removing the battery pack from the vehicle. Battery tests are performed on at least some of the plurality of batteries and a battery test result for each of the batteries tested are obtained and stored in a database. A plurality of replacement batteries are tested and test results for each of the replacement batteries are stored in the database. The battery test results from the database are retrieved and used to create a refurbished battery pack. An apparatus includes a database for storing test results.

The invention relates to the field of battery testing, in particular to a battery testing device and method for new energy automobile maintenance, and the testing device comprises a testing table, the upper end of the testing table is fixedly provided with a storage rack, the storage rack is internally provided with a clamping assembly, the two sides of the upper end of the testing table are fixedly provided with lifting cylinders, and the top ends of the lifting cylinders are provided with longitudinal guide rails. A rotating motor is fixedly arranged at the bottom in the mounting pedestal; the output end of the rotating motor is fixedly connected with a rotating seat; a testing bracket is rotatably arranged in the rotating seat; sliding grooves are formed in two ends of the testing bracket; and a test assembly is arranged in the sliding seat. According to the invention, by adjusting the test spacing between the test assemblies, different numbers of battery cells of the to-be-tested battery can be tested independently according to actual test requirements, and the adaptability in the test process is effectively improved.

The invention relates to the technical field of batteries, and discloses a battery charge state estimation method and device, equipment and a storage medium. The method comprises the following steps: constructing a fractional order equivalent circuit model of a to-be-tested battery; constructing a first state equation set according to the fractional order equivalent circuit model, and discretizing the first state equation set to obtain a second state equation set; performing parameter identification on the fractional order equivalent circuit model by adopting a particle swarm optimization algorithm; and estimating the state of charge of the to-be-tested battery by adopting a self-adaptive extended Kalman filtering algorithm according to the second state equation set after the parameters are identified. According to the method, the equivalent circuit model is constructed by adopting the fractional order model, the fractional order model can better reflect the nonlinear characteristic of the battery, so that the precision of the circuit model is improved, and on the basis of the established equivalent circuit model, the state of charge is estimated in combination with the adaptive fractional order extended Kalman filtering algorithm, so that the accuracy of the circuit model is improved. Therefore, the accuracy of state-of-charge estimation can be improved.

The invention discloses a battery capacity performance testing method and device and a storage medium, and relates to the technical field of battery capacity performance testing. By constructing a dynamic load model and a multi-load test protocol and combining a high-precision data acquisition and filtering algorithm, adaptive data analysis and a machine learning regression model, the problems of difficulty in balancing precision and efficiency, large data acquisition error, fixed test protocol and the like in the traditional battery test are solved; by dynamically adjusting test parameters and environmental conditions, complex working conditions of the battery in actual use are accurately simulated, meanwhile, dynamic updating and optimization of a test protocol are achieved, the test precision, the data reliability and the test efficiency are remarkably improved, and a comprehensive, efficient and high-adaptability solution is provided for battery performance evaluation and health management.

The present disclosure discloses a battery SOC estimation method and apparatus. The method includes: calling an equivalent circuit model of a to-be-tested battery, and acquiring offline parameters of the to-be-tested battery; calculating alternately a first SOC value of the to-be-tested battery and online parameters of the to-be-tested battery based on the equivalent circuit model and the offline parameters, and selecting the first SOC value, obtained after the calculation is performed for a preset number of times, as an SOC estimation value; and calculating a current SOC value of the to-be-tested battery according to the SOC estimation value. By using an embodiment of the present disclosure, problems of accuracy reduction and an SOC jump, caused by only using the offline parameters to estimate an SOC, are solved, and influence of electric current accuracy and temperature, caused by only using an ampere-hour integration method, is reduced, thereby improving estimation accuracy and stability.

The invention provides a method for predicting the residual life of a decommissioned power battery cell, and the method comprises the steps: carrying out the impedance testing of different frequencies of a to-be-tested battery cell in a decommissioned power battery in a preset testing frequency range, obtaining the impedance response data at different frequencies, and obtaining the impedance spectrum data; utilizing scene conditions corresponding to different steps are obtained, the utilizing scene conditions comprise the temperature range and the charging and discharging multiplying power, and a target step utilizing scene is matched in combination with the step grade to which the current to-be-detected battery cell belongs; performing associated storage on the target step utilization scene and the model, capacity, internal resistance and impedance spectrum data information of the retired battery cell to form a retired battery step utilization scheme; if it is detected that the battery is in an abnormal state, an early warning mechanism is triggered, and corresponding safety protection measures including cutting off a power source and starting a cooling system are taken according to a preset processing strategy.

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.

The invention discloses a battery capacity prediction and state evaluation method and system based on multi-model collaborative learning, and belongs to the technical field of battery management. The method comprises the following steps: constructing a database containing multiple lithium ion battery long-term cycle data, and classifying according to a capacity attenuation trend; cleaning and preprocessing short-term cycle data of the to-be-tested battery; matching the to-be-tested data with the long-term attenuation trend in the database by using a clustering algorithm, and determining an optimal matching trend; distributing weights for the data in the matching trend by adopting a correlation algorithm, and generating initial capacity attenuation prediction; performing sequence correction on the preliminary prediction in combination with meta-learning and a related model, and generating a smooth future attenuation trend conforming to a physical law; and outputting a capacity prediction and health state evaluation result, and evaluating the prediction precision through a root-mean-square error and an average absolute percentage error. The method significantly improves the precision and generalization ability of long-term capacity prediction, and is suitable for various scenes such as electric vehicles, energy storage systems, consumer electronics and the like.

The invention discloses a communication simulation device for simulating a front-end chip in a battery management system, and relates to the technical field of communication testing, the communication simulation device comprises a micro-control unit, a field programmable logic gate array and a daisy chain conversion module which are connected in sequence; the field programmable logic gate array is used for simulating a register of an analog front-end chip in the battery management system and a daisy chain communication time sequence based on the register configuration parameters; the micro-control unit is used for communicating with an upper computer, receiving a register configuration parameter modification instruction of the upper computer, and modifying register configuration parameters in the field programmable logic gate array according to the register configuration parameter modification instruction; the register configuration parameters in the field programmable logic gate array are uploaded to the upper computer; and the daisy chain conversion module is used for communication between the field programmable logic gate array and the tested battery control unit. According to the invention, the test safety can be improved.

The utility model provides an energy storage twin trawling test system. The energy storage twin trawling test system comprises a first test unit, a second test unit and an isolation transformer, the first test unit comprises a first test battery system, a first test battery management system and a first energy storage converter; the second test unit comprises a second test battery system, a second test battery management system and a second energy storage converter; the first test unit and the second test unit are connected through corresponding energy storage converters; the first test unit and the second test unit are electrically connected with a secondary winding of the isolation transformer through the corresponding energy storage converters respectively; and the primary winding of the isolation transformer is connected with the low-voltage side of the power grid. According to the invention, independent shutdown can be realized when any test unit fails, and the other test unit can be switched to a zero-power operation mode to realize fault interlocking when any test unit fails to stop, so that tripping of a grid-connected transformer switch due to reverse power of a grid-connected point is avoided.

The invention discloses a lithium ion battery health state estimation method and system based on unsupervised transfer learning and electronic equipment, and the method comprises the following steps: selecting two different types of batteries, and determining a source domain battery and a target domain battery; obtaining a loop test data set, and further obtaining a sample set and a label set; performing data processing on the sample set and the label set to obtain a training verification data set; using the training verification data set to train a domain adversarial neural network model; inputting cycle test data of the battery to be tested into the domain adversarial neural network to obtain an estimation result; according to the method, the cycle test data and the calibration test data of the existing active domain battery and a small amount of cycle test data of the target domain battery without calibration test are utilized, a redundant target domain battery cycle test process is omitted, and accurate estimation of the health state of the target domain battery is realized.

The invention relates to the field of battery management, and discloses an intelligent voltage regulation type battery output current control method and system, and the method comprises the steps: obtaining a load demand corresponding to a tested battery, determining an application working condition, setting an initial regulation voltage, constructing a simulation regulation and control environment, monitoring a real-time current, and calculating current deviation values of different working conditions; a voltage regulation strategy is formulated, multi-round on-load testing is carried out, and current load indexes are counted to construct an efficiency control system, so that the discharge response effect is analyzed, the voltage change trend is inquired, and core change elements are identified; and then connecting the intelligent feedback regulation unit with the test battery to form a group, collecting running dynamic current data, screening controllable current nodes, and finally generating a current control scheme adaptive to the test battery. The control efficiency of the output current of the battery can be improved.

The invention discloses a battery health state prediction method, which comprises the following steps of: testing calendar life capacity fading rates of a plurality of sample batteries at a plurality of preset temperatures and a plurality of preset SOC (State of Charge) intervals, and establishing a capacity fading rate-time database; acquiring a first time counting matrix of the to-be-tested battery in an operation state and a second time counting matrix of the to-be-tested battery in a dormant state; respectively converting a first time matrix and a second time matrix according to the first time counting matrix, the first time step length, the second time counting matrix and the second time step length, and adding the corresponding time of the two time matrixes to obtain a total time matrix; according to a capacity fading rate-time database, searching a capacity fading rate corresponding to each time in the total time matrix, and obtaining a capacity fading rate matrix; and according to the capacity attenuation rate matrix, calculating to obtain a health state matrix of the to-be-tested battery. According to the invention, the accuracy of battery health state prediction can be improved. The invention further provides a battery management system and a new energy automobile.

The invention provides a method and a device for determining the health state of a battery, which can be used in the field of electrochemical energy storage. Receiving a state determination instruction for the target battery; in response to the state determination instruction, determining a target sound wave characteristic value according to multiple groups of target receiving signals carried in the state determination instruction and a signal characteristic value corresponding to each target receiving signal; determining a target state characterization value corresponding to the target battery according to a target characterization value mapping rule and the target sound wave characteristic value; wherein the target characterization value mapping rule is obtained by performing fitting processing on parameters in a relational expression of sound wave characteristic values and state characterization values according to the state characterization values, corresponding to each health state, of the tested battery and the sound wave characteristic values; and determining a battery health state value of the target battery according to the first initial state characterization value of the target battery and the target state characterization value. Based on the method, the battery health state value can be determined more efficiently and quickly according to the target representation value mapping rule.

The utility model discloses an electric bicycle battery testing device. The electric bicycle battery testing device comprises a charging module, a discharging module, a charging switch module, a discharging switch module, an acquisition module, a control module and an analysis module. The charging module and the discharging module are connected with a to-be-tested battery. The charging switch module is connected between the charging module and the power supply; the discharge switch module is connected between the discharge module and the control module; the control module is connected with the charging switch module, the control module is also connected with the discharging switch module, the acquisition module is arranged in a battery to be tested, and the control module is connected with the acquisition module; the acquisition module is used for acquiring test parameters of a to-be-tested battery; the control module charges or discharges the to-be-tested battery according to the test parameters; and the analysis module is connected with the acquisition module and determines a test result of the to-be-tested battery according to the test parameters. The electric bicycle battery testing device provided by the embodiment of the utility model is beneficial to improving the testing efficiency and accuracy.

Systems and methods are provided for testing and / or validating anti-propagation systems designed to mitigate a thermal runaway condition in lithium-ion batteries. A system comprises a first temperature sensor for detecting a temperature of a trigger battery cell within the battery module and a heater removably couplable to a substantially central portion of the trigger cell and configured to heat the trigger cell to a threshold temperature. The system further comprises a second temperature sensor for detecting a temperature of a test battery cell adjacent to the trigger cell within the battery module. The trigger cell undergoes a thermal runaway condition upon reaching the threshold temperature. The system may further comprise a controller for controlling the rate of heating of the trigger cell. The system ensures that the trigger cell will breach via the pressure release valve or cell vent after reaching the threshold temperature.

The invention provides a zero-carbon battery charging and discharging test system and method. The system comprises a plurality of energy storage energy modules, a plurality of energy allocation modules connected with the plurality of energy storage energy modules, a plurality of non-isolated high-efficiency charging and discharging machines, a plurality of test side intelligent switches connected with the plurality of non-isolated high-efficiency charging and discharging machines, and a plurality of tested batteries connected with the plurality of non-isolated high-efficiency charging and discharging machines. The first controller is used for collecting state information of the plurality of energy storage energy modules and controlling working states of the plurality of energy allocation modules so as to adjust electric energy exchange between the plurality of energy storage energy modules and the direct current bus; the DC bus is connected with the plurality of energy allocation modules and the plurality of test side intelligent switches, and is used for establishing an electric energy transmission path between the plurality of energy storage energy modules and the plurality of tested batteries. And the second controller is connected with the plurality of test-side intelligent switches and is used for controlling on and off of the plurality of test-side intelligent switches so as to realize charging and discharging tests of the plurality of tested batteries.

The invention provides a Bluetooth equipment battery endurance test method, which is characterized in that a Bluetooth signal is sent and / or received through a Bluetooth adapter, a voltage value of a battery is acquired through a power supply monitoring module, and the method comprises the following steps: when a user tests Bluetooth equipment, the Bluetooth signal and the voltage value of the Bluetooth equipment are acquired; determining the device type of the Bluetooth device according to the Bluetooth signal, and determining an operation instruction through the Bluetooth device type; performing power consumption operation on the Bluetooth equipment according to the operation instruction; and determining the endurance of the battery of the Bluetooth equipment according to the Bluetooth signal and the change of the voltage value. The Bluetooth signal and the voltage value are acquired at the same time, so that the cruising ability of the Bluetooth equipment is measured, a real use scene is simulated, the Bluetooth equipment is fully automatically tested, manual operation is not needed in the process, and the test is efficient and accurate.

The utility model discloses a needling mechanism and a battery thermal runaway testing device. The needling mechanism comprises a needle body, a heating piece and a first temperature sensor. The needle body is used for puncturing a to-be-tested battery; the heating piece and the needle body transfer heat; the first temperature sensor is used for acquiring the temperature in the to-be-measured battery. The acupuncture test is carried out under the high-temperature condition, and in order to track the temperature change in the battery in real time, the first temperature sensor is arranged in the embodiment, so that the temperature in the battery to be tested is obtained in real time. In this way, the internal temperature change of the to-be-measured battery at different pricking needle positions can be obtained. The needle body punctures at different temperatures, and the internal temperature of the to-be-tested battery is changed; the performance of the to-be-tested battery under extreme conditions can be obtained to the maximum extent through the needle body in different needling directions, the internal temperature change of the to-be-tested battery and the like, and higher safety and reliability of the battery in practical application are further ensured.

The invention discloses a large model and sequence matching-based battery health state evaluation method and system. The method comprises the following steps of: classifying battery health states according to a numerical range; extracting a charging sequence in a general form from the test battery monomers, and defining the charging sequence as a current sequence; the method comprises the following steps: extracting charging sequences with different median thresholds in a general form from known single batteries, and defining the charging sequences as candidate sequences; performing sequence matching on the current sequence and each candidate sequence; performing fine tuning on the large language model by adopting a matching sequence with a tag; and acquiring actual charging data of the to-be-tested single battery, extracting a charging sequence in a general form as a current sequence, performing sequence matching on the current sequence and each candidate sequence, and obtaining an evaluation category of the health state of the battery by using a fine-tuned large language model. According to the method, the numerical range of the health state of the battery is used as a state evaluation result, and the problem that the confidence coefficient of the method is reduced due to outlier estimation values in a traditional estimation method is solved.

The invention discloses a calibration method for a battery internal resistance tester, and the method comprises the following steps: S1, carrying out the N times of measurement of the standard resistance through a battery internal resistance tester in a standard temperature environment, and constructing a training sample; s2, for M standard resistors with different resistance values, repeatedly executing the step S1 to obtain M training samples; s3, in environments with different temperatures, the step S2 is executed repeatedly, and a training set is constructed; s4, constructing a battery internal resistance tester calibration model based on a neural network algorithm and training the battery internal resistance tester calibration model; and S5, when the battery internal resistance tester is used for carrying out actual measurement, carrying out N times of measurement on the to-be-tested battery, then constructing a feature vector of the to-be-tested battery internal resistance tester, inputting the feature vector into the trained battery internal resistance tester calibration model to obtain a deviation, and compensating a measurement result by using the obtained deviation. According to the method provided by the invention, the deviation at different temperatures can be predicted and compensated, and the precision of the battery internal resistance tester is effectively improved.

The invention belongs to the technical field of batteries, and discloses a cooling clamp for battery testing, a battery testing device and a battery testing method. The cooling clamp for battery testing comprises a supporting piece, the supporting piece is connected with a first clamping piece and a second clamping piece, a clamping space is formed between the first clamping piece and the second clamping piece, a to-be-tested battery is used for being clamped in the clamping space, and in the first clamping piece and the second clamping piece, the clamping space between the first clamping piece and the second clamping piece is larger than the clamping space between the first clamping piece and the second clamping piece. At least one of the heat conduction pieces is a heat conduction piece, and the heat conduction piece is matched with the to-be-tested battery in a heat exchange mode so as to absorb heat from the to-be-tested battery. The cooling clamp can clamp and fix the battery and absorb heat generated in the charging and discharging process of the battery, the temperature of the battery is prevented from being too high in the cyclic charging and discharging process of the battery, and the cycle performance, the service life and the test efficiency of the battery are improved.

The present disclosure teaches a solid-state battery testing device that provides uniform pressure over the test cell and provide a hermetic seal to protect the cell. The solid-state battery testing device includes a cell module, a pressure control module, and an environment control module. The pressure control module utilizes a single lead screw and the cell module contains a swivel-type plunger assembly to apply uniform pressure to a solid-state battery contained within the cell module. The environment control module utilizes all inorganic components to provide a low leak-rate and cost-effective sealing solution.

A battery internal temperature information processing method, a computer device, and a storage medium that first acquire off-line testing data for off-line testing a battery module and construct an equivalent thermal network model from the off-line testing data, determine optimal model parameters of the equivalent thermal network model based on a multi-objective function fitting method; thereafter, a first battery internal temperature estimate of the battery of the vehicle at a first moment in actual operation of the vehicle is determined, in turn, based on the acquired initial state vector values of the battery of the vehicle, first operational data at a first moment in actual operation of the vehicle, and an equivalent thermal network model including the optimal model parameters.

The invention provides a passenger car battery low-temperature heating test system, method, device and equipment and a medium, and the system comprises a passenger car battery low-temperature heating test system which is composed of a whole car domain controller, a control assembly and a BMS battery management subsystem, and the method comprises the steps: carrying out the whole car power-on of a target passenger car according to a passenger car test request for the low-temperature rapid heating of a battery; the battery temperature and the vehicle running state of the target passenger car are obtained, the battery temperature is judged based on the temperature interval, and at least one judgment node of heating needing and heating not needing is obtained; when the judgment result is that heating is needed, determining a heating gear and a target temperature according to the temperature interval of the battery temperature; and heating the target battery to the target temperature according to the heating gear. The device has the beneficial effects that the power battery of the vehicle can be rapidly heated in an extremely low temperature environment, and the self-heating test of the test battery is realized.

The invention discloses a battery pack test method, a storage medium and electronic equipment, and relates to the field of batteries. The method comprises the following steps: carrying out a charge-discharge test on a to-be-tested battery pack, and obtaining long-cycle test data of the to-be-tested battery pack; performing test condition analysis on the long-cycle test data to check whether the to-be-tested battery pack has an abnormal point, and outputting an abnormal point check result; and inputting the long-loop test data into a preset algorithm program under the condition that the abnormal point checking result is passed, and obtaining a test performance report of the to-be-tested battery pack according to the preset algorithm program. According to the invention, the problem of low long-cycle test efficiency of the battery pack in the prior art is solved.

The invention discloses a battery lithium precipitation judgment method, which comprises the following steps: determining a first characteristic frequency and a second characteristic frequency of a battery to be detected, the first characteristic frequency being a frequency corresponding to a junction point of an arc part and a straight line part in a Nyquist diagram of the battery to be detected, and the second characteristic frequency being a frequency corresponding to a junction point of an arc part and a straight line part in a Nyquist diagram of the battery to be detected; the second characteristic frequency is the frequency corresponding to a point of which the imaginary part of the arc part is zero in the Nyquist diagram; obtaining first real part data of the impedance at the first characteristic frequency and second real part data of the impedance at the second characteristic frequency of the to-be-tested battery in different preset charge states; according to the first real part data and the second real part data, acquiring electrochemical transfer internal resistance in different preset charge states; judging whether the electrochemical transfer internal resistance tends to increase and then decrease along with the increase of the preset charge state, and if so, determining that the to-be-detected battery generates lithium precipitation; if not, lithium precipitation does not occur. And whether lithium precipitation occurs in the battery can be quickly and accurately judged. The invention further discloses a lithium precipitation judgment device, electronic equipment and a readable storage medium.

The invention discloses a battery health state assessment method and device, electronic equipment and a storage medium, and belongs to the technical field of battery state assessment, and the method comprises the steps: determining a time constant corresponding to each peak value in a time domain distribution diagram of a sample battery impedance spectrum; determining a frequency point corresponding to the peak value according to the time constant, and obtaining dynamic impedance corresponding to the frequency point in the charging and discharging process of the sample battery; constructing a neural network model by taking the dynamic impedance of the battery as input and the residual capacity of the battery as output, and performing iterative training on the neural network model according to the dynamic impedance and the residual capacity of the sample battery to obtain a target neural network model; and performing health state evaluation on the to-be-tested battery based on the target neural network model. According to the method, the frequency point is determined through the time constant corresponding to the peak value of the time domain distribution diagram of the impedance spectrum, the health state of the battery is evaluated according to the dynamic impedance corresponding to the frequency point in the charging and discharging process, and accurate and efficient evaluation of the health state of the battery is achieved.

The invention relates to a test battery cell (14) for selectively triggering a thermal runaway of the test battery cell (14), wherein the test battery cell (14) comprises a cell housing (16) that separates a cell interior (18) from an environment (20) of the test battery cell (14), and an electrode layer arrangement (26) arranged in the cell interior (18) comprising at least a cathode layer (52), an anode layer (50) and a separator layer (28) arranged between the cathode layer (52) and the anode layer (50).The test battery cell (14) has an electrically conductive induction element (46) inside the cell (18), which is arranged in contact with at least a first section (46a) of the induction element (46) within the electrode layer arrangement (26) on a separator layer area (28a) of the separator layer (28), and which can be heated by electrical induction using a cell-external induction device (48) such that the separator layer area (28a) is damaged.

The invention provides a battery thermal runaway early warning method and system, vehicle-mounted equipment and a storage medium, and the method comprises the steps: obtaining the working condition data of a to-be-detected battery, the working condition data comprising state data and environment data of an environment where the to-be-detected battery is located, and the state data comprising a temperature parameter, an electrical parameter, a health state parameter and a charge state parameter; the working condition data are input into the battery thermal runaway simulation model, thermal runaway simulation is conducted on the to-be-tested battery, the early warning parameter extreme value of the to-be-tested battery under the working condition data is obtained, the early warning parameter extreme value comprises the temperature parameter extreme value, and the battery thermal runaway simulation model is constructed through the thermal performance of the battery under various working condition data in the whole life cycle; and comparing the temperature parameter with the temperature parameter extreme value, and carrying out battery thermal runaway early warning according to a comparison result. Through the battery thermal runaway simulation model in the full life cycle of the battery, accurate early warning of thermal runaway can be realized according to the working condition data of the battery for the batteries with different health states and charge states.