1096 results about "Battery voltage" patented technology

The invention discloses a control system for lithium battery power management, and relates to the field of lithium battery control, and the system comprises a voltage input module which is used for externally connecting voltage and supplying power to a battery power supply module and a time delay module; the battery power supply module is used for charging the battery; receiving the battery voltage information, and adjusting the voltage output to the battery according to the battery voltage; the battery module is used for a battery to store electric energy; compared with the prior art, the system has the beneficial effects that the output voltage of the battery power supply module is adjusted through the feedback module, the output voltage of the battery power supply module is relatively large at the beginning, and the charging voltage is reduced along with the increase of the battery voltage, so that a quick charging effect is constructed; whether battery charging is abnormal or not is detected through the time delay module and the charging fault detection module, the battery power supply module is adjusted to perform constant-voltage charging when charging is abnormal, and the battery charging effect is guaranteed.

The invention discloses a three-phase vehicle-mounted charger hierarchical control method and system based on a battery state, and the method comprises the steps: obtaining the battery state data of a vehicle-mounted power battery, the battery state data at least comprising a battery voltage and a battery charge state; determining a charging mode according to the battery voltage and / or the battery charge state; when the charging mode is a first charging mode, controlling the PFC converter to operate in a constant voltage output mode, and executing voltage following control on the bidirectional DC-DC converter based on the battery voltage; and when the charging mode is a second charging mode, executing voltage following control on the PFC converter based on the battery voltage, and controlling the bidirectional DC-DC converter to operate in a constant-frequency or constant-phase output mode at the same time. By setting hierarchical control strategies under different working conditions, the output voltage of the PFC converter is adaptively adjusted, the voltage regulation transformation ratio under different working conditions is optimized, the overall circuit structure is improved, and the charging efficiency of the vehicle-mounted charger within the full working condition range is improved.

The invention relates to the technical field of energy storage lithium batteries, in particular to a method for detecting the health state of a household energy storage lithium battery. The method for detecting the state of health of the household energy storage lithium battery is characterized by comprising the following specific steps: S1, preprocessing charge-discharge cycle data; s2, performing multi-domain feature extraction; s3, an SA-XGBoost model oriented to static data and a TSO-LSTM-AM model oriented to dynamic data are constructed respectively, and SOH estimation is carried out on the SA-XGBoost model and the TSO-LSTM-AM model; and S4, finally, performing compression optimization on the model through knowledge distillation and quantification technologies to meet a lightweight deployment requirement. Compared with the prior art, in combination with historical charging and discharging parameters such as battery voltage, current and temperature, feature vectors are constructed through adaptive data cleaning and multi-domain feature extraction, the SOH estimation capability of static and dynamic data is optimized by adopting machine learning and a deep learning model respectively, and the deployment requirement of practical application is met by utilizing a model compression technology.

The invention discloses an internet of things data optimization processing method and device and a medium, and relates to the technical field of internet of things edge computing, and the method comprises the steps: collecting a battery voltage, a CPU utilization rate and a network bandwidth of an internet of things device in real time, calculating an available energy consumption budget, and configuring a basic sampling frequency; acquiring a time sequence data stream by using a basic sampling frequency, measuring a nonlinear information entropy increment through a sliding window, and dynamically evaluating the information value density of the time sequence data stream; according to a comparison result of the information value density and the available energy consumption budget, obtaining an optimal sampling frequency, and performing time sequence data flow anomaly judgment to generate a time sequence data subset; and inputting the time sequence data subset into the pulse neural network, calculating a current continuous data point variation, and activating a processing channel if the current continuous data point variation exceeds a device dynamic threshold. According to the method, the basic sampling frequency is configured through the non-cooperative game model, and combined modeling and game optimization of the equipment operation state and resource constraint are realized.

The invention belongs to the technical field of water traffic transportation safety and navigation mark navigation aiding, and mainly relates to a navigation mark anti-collision early warning method based on multi-sensor fusion, and the method comprises the steps: constructing a multi-sensor fusion architecture integrating an AIS terminal, a laser radar and an AI camera, and achieving the omnibearing monitoring and precise recognition of a ship in a navigation channel; a grading response mechanism is adopted, corresponding functions are dynamically started according to the real-time distance between the ship and the navigation mark, and targeted response from early warning to emergency warning is achieved; a legal evidence chain packaging mechanism is introduced, a unique ID is generated for each early warning event, formatted evidence is stored in an associated mode, and integrity and traceability of data are ensured; through a dynamic energy supply strategy, an equipment operation mode is intelligently adjusted according to a storage battery voltage threshold value, and continuous and stable work of the system under the conditions of cloudy and rainy days, night and the like is guaranteed; according to the invention, the accuracy, timeliness and reliability of navigation mark collision early warning information are effectively improved.

The invention provides a lithium battery residual life detection method and apparatus, an electronic device and a storage medium. The method comprises the steps of performing correlation analysis on a voltage battery capacity curve of each charging interval and a battery health state to obtain a correlation coefficient; when the absolute value of the correlation coefficient is greater than a preset value, constructing a battery voltage characteristic sample set through the battery voltage and the battery capacity of the charging interval, and taking impedance spectrum data corresponding to each charging interval in the battery voltage capacity characteristic sample set as an impedance spectrum characteristic sample set; inputting the battery voltage characteristic sample set into a deep learning model to obtain a predicted impedance spectrum, and training the deep learning model based on the predicted impedance spectrum and the impedance spectrum characteristic sample set; and inputting the charging data of a to-be-predicted lithium battery into the trained deep learning model to obtain a target predicted impedance spectrum, and determining the predicted residual life of the lithium battery based on the equivalent circuit model and the target predicted impedance spectrum. The detection efficiency is improved by detecting the battery voltage characteristics of the lithium battery.

The embodiment of the invention discloses a super charging interface metrological verification device and method, and the device comprises a communication simulation unit which communicates with a super charging pile and is used for controlling the starting or stopping of a charging process. And the charging interface control simulation unit is used for being electrically connected with the super charging pile and providing a corresponding electrical parameter acquisition interface. And the programmable load unit is used for simulating a power battery load of the electric vehicle and receiving the electric energy transmitted by the charging interface control module. And the battery voltage simulation unit is connected with the interface control simulation unit of the charging interface control module and is used for simulating the battery voltage of the electric automobile. And the electric energy metering unit is electrically connected with the charging interface unit and is used for performing electric energy metering detection on the process of acquiring the electric energy by the programmable load unit to obtain an electric energy detection result. According to the invention, the metrological verification problems of large transient power and short charging time of a super charger of an existing charging facility are solved, and the metering accuracy of a high-power charging interface is effectively guaranteed.

A battery management system includes a sensing unit to generate a sensing signal indicating a battery voltage and a battery current of a battery, a memory unit to store a charge map recording a correlation between first to nth reference state of charge (SOC) ranges, first to nth reference currents and first to nth reference voltages for multi-stage constant-current charging, and a control unit to change to constant voltage charging using a kth reference voltage corresponding to a kth reference SOC range in response to the battery voltage having reached the kth reference voltage during constant current charging using a kth reference current corresponding to the kth reference SOC range to which an SOC of the battery belongs. The control unit updates the kth reference current of the charge map based on a time-series of the battery current in a charging period of the constant voltage charging.

The invention relates to an automobile power battery voltage abnormity detection method and a vehicle. The method comprises the following steps: acquiring multi-dimensional battery operation data of an automobile power battery corresponding to different time lengths, and acquiring weighted abnormal depth data of the automobile power battery corresponding to a target dimension according to the multi-dimensional battery operation data; for each time length, inputting the multi-dimensional battery operation data and the weighted abnormal depth data corresponding to the time length into a pre-constructed battery voltage abnormal detection model matched with the time length, and obtaining a plurality of voltage predicted values of the time length corresponding to different quantiles through the battery voltage abnormal detection model; and according to the plurality of voltage prediction values corresponding to each time length, obtaining a voltage anomaly detection result of the automobile power battery. By adopting the method, the reliability of a battery voltage anomaly detection result can be improved.

The invention relates to the field of battery management systems, and particularly discloses a battery equalization-alternating current self-heating integrated topology based on electromagnetic induction and a control method, the topology comprises a battery pack, a switch array, a multi-winding transformer, a signal acquisition and processing module, a control unit and a driving circuit, energy balance in the battery modules and among the modules is realized through the multi-winding transformer, and the same transformer winding is utilized to generate alternating current at low frequency to realize self-heating of the battery; the control method is based on battery voltage and temperature information, balancing and heating modes are dynamically switched, and flexible control over the heating rate and the balancing speed is achieved by adjusting PWM parameters. The system is high in integration level, does not need an external power supply, is high in expansibility, and is suitable for efficient thermal management and state equalization of various lithium ion battery systems in a low-temperature environment.

The invention discloses a lithium ion battery formation pretreatment process based on positive electrode lithium supplement. The process comprises the following steps: preparing a battery cell comprising a positive electrode, a negative electrode and a diaphragm; the positive electrode comprises a positive electrode lithium supplement agent; injecting an electrolyte into the battery cell, and standing the battery cell, so that the battery cell fully infiltrates the electrolyte to obtain a battery; carrying out constant-current charging until the battery voltage reaches the initial gas production potential V1 of the positive electrode lithium supplementing agent; stopping charging after the voltage of the battery reaches V1, and vacuumizing the battery for the first time; carrying out constant-current charging until the battery voltage reaches the peak gas production potential V2 of the positive electrode lithium supplementing agent; stopping charging after the voltage of the battery reaches V2, and vacuumizing the battery for the second time; performing constant-current charging until the voltage of the battery reaches the gas production cut-off voltage V3 of the positive electrode lithium supplement agent; and stopping charging after the voltage of the battery reaches V3, and vacuumizing the battery for the third time and sealing the battery at the same time. The comprehensive performance of the lithium ion battery is remarkably improved, the process is simple, the lithium ion battery can be easily integrated into an existing production line, and the high industrialization value is achieved.

The invention provides an engine VVT clamping stagnation processing method and system, and the method comprises the steps: obtaining the static characteristics and dynamic response characteristics of an engine during operation, detecting the operation state of the engine VVT, and judging whether the VVT clamping stagnation exists or not; if VVT clamping stagnation does not exist, according to the set period, the oscillation amplitude and the oscillation frequency, a battery valve is driven to enable a VVT actuator to do reciprocating motion within the stroke range; if VVT clamping stagnation exists, a corresponding voltage compensation coefficient is obtained according to the real-time storage battery voltage, and oscillation is performed by adopting a strong oscillation mode or a limit position recovery mode based on the voltage compensation coefficient; and detecting the triggering times of oscillation, judging whether the VVT clamping stagnation is solved or not when the triggering times reach a triggering times threshold value, if so, entering PID control, and if not, judging that the VVT has a fault. By means of the method, VVT clamping stagnation can be prevented and repaired in the early stage, and the VVT fault rate and engine performance fluctuation are reduced.

The invention discloses an energy storage battery aging evaluation method and device under an immersed liquid cooling condition, terminal equipment and a storage medium, and belongs to the field of battery testing. The method comprises the steps of obtaining a first active lithium ion loss change rate and a first active substance loss change rate according to a battery voltage and a first battery capacity identification characteristic peak in a to-be-tested battery test, and calculating a battery capacity loss change rate according to a first battery capacity and a second battery capacity before the test; determining a second active lithium ion loss change rate, a second active material loss change rate and a battery impedance change rate based on the electrochemical impedance spectrogram and the pre-test impedance, and determining the battery capacity loss change rate and the battery impedance change rate according to the determined active lithium ion loss, the active material loss, the battery capacity loss change rate and the battery impedance change rate. The resistance, the moisture content and the dielectric loss change rate of the cooling liquid to be measured construct an analytic hierarchy model, the battery aging condition is determined according to the calculated aging evaluation value, and the problem that deviation exists in single evaluation in the prior art is solved.

The invention relates to the technical field of energy storage fault diagnosis, in particular to a multi-type fault diagnosis method for electrochemical energy storage. According to the method, parameters such as battery voltage, temperature distribution, internal resistance change and state of charge are collected, a multi-fault coupling feature space is constructed, and correlation mapping relations such as overcharge-temperature abnormity, connection fault-local high temperature and aging-internal resistance change are established; an improved salat swarm optimization algorithm is adopted, and uniform initialization, dynamic path search and bidirectional optimization strategies are introduced, so that the search precision and convergence performance are improved; constructing a multi-scale multi-layer neural network, fusing monomers, modules, clusters and system-level features, and performing connection initialization based on association mapping weights; and finally, fault classification, probability weighted fusion and causal chain traceability are realized, and primary and secondary faults and grades are output. According to the method, the coupling fault identification accuracy and the early warning advance are improved, the false alarm rate is reduced, and the method has engineering application value.

The invention discloses a hydrogen fuel cell optimization algorithm based on particle swarm optimization of an integrated system, and belongs to the technical field of micro-grid energy management. An existing hydrogen fuel cell has the problems of low fuel utilization rate, slow response speed and the like under a dynamic load condition. In order to solve the problem, a hybrid energy system topology consisting of a photovoltaic (PV), a proton exchange membrane fuel cell (PEMFC), a lithium ion battery (BAT) and a super capacitor (SC) is constructed, and mathematical models, including a photovoltaic output power model, a fuel cell voltage model and a cell state-of-charge model, of all energy units are established. A PI controller is designed for a fuel cell, and a proportional gain KP and an integral gain KI of the fuel cell are dynamically adjusted through a particle swarm optimization (PSO) algorithm. Specifically, PI parameters are coded into particle position vectors, a multi-target fitness function is constructed, and hydrogen consumption, system stability and oxygen utilization rate are comprehensively considered; and a dynamically adjusted inertia weight mechanism is adopted to guide particle search, and iterative optimization is realized. After optimization, parameters are written into a PI controller in real time, and the hydrogen and air flow is accurately adjusted. Meanwhile, a continuous monitoring mechanism is introduced, when the photovoltaic power fluctuation exceeds 10%, re-optimization is automatically triggered, and closed-loop control is formed. The method improves the fuel utilization rate and the reaction rate of the fuel cell, is suitable for the dynamic load micro-grid, and improves the overall efficiency and stability of the system.

The invention discloses a battery charging control method and a charging system. The method comprises the following steps: acquiring a battery voltage and a battery temperature, and determining a target jump voltage interval in which the battery voltage falls; determining candidate charging multiplying power corresponding to the battery voltage and the battery temperature from the plurality of charging multiplying power according to a charging multiplying power lookup table; taking a smaller value from a preset charging rate upper limit and a candidate charging rate corresponding to the target jump voltage interval as a target charging rate; according to the target charging rate and the rated battery capacity, a charging current is requested from the power supply equipment to charge the battery, and the voltage of the charged battery and the temperature of the charged battery are obtained; and updating the battery voltage by using the charged battery voltage and updating the battery temperature by using the charged battery temperature, and returning to the step of determining the target jump voltage interval in which the battery voltage falls until the battery is charged. According to the embodiment of the invention, the charging efficiency of the battery can be improved.

The present invention provides a battery module that avoids interference between the wiring and the housing, etc., and facilitates miniaturization, in a battery module equipped with wiring for measuring the voltage of each of the multiple stacked battery cells. [Solution] The device includes a plurality of stacked battery cells 3, a plurality of connecting terminals 4 connected one-to-one to tabs extending from the battery cells 3 or to busbars 33 connecting the tabs, a plurality of insulating connection parts 7 arranged in the same number as the connecting terminals 4 in a direction perpendicular to the stacking direction, a plurality of plug pins 8 supporting the plurality of connection parts 7 and electrically connected to a voltage measuring means (not shown), and a plurality of flexible wirings 5 ​​for voltage measurement that connect the connecting terminals 4 and the connection parts 7 one-to-one, wherein the plurality of plug pins 8 and the plurality of wirings 5 ​​are electrically connected to each other one-to-one, and the wirings 5 ​​are connected to the connecting terminals 4 in a state where they extend from the connection parts 7 in a direction along the stacking direction.

The aerosol generating device includes a battery, a DC / DC converter configured to boost the voltage of the battery to supply a boosted voltage to the first heater and the second heater, a first resistor circuit connected in series with the second heater and used to sense the current flowing through the second heater, a second resistor circuit connected in series with the first resistor circuit and used to reduce the peak value of the current flowing through the second heater, an operation switch that determines whether to pass current through the second heater, and a processor for controlling the battery, the DC / DC converter, and the operation switch.

The utility model discloses a double-screw water gate, which comprises an outer frame, a storage battery, a photovoltaic panel and a controller, the storage battery, the photovoltaic panel and the controller are positioned on the outer frame, a gate plate is slidably arranged on the inner side of the outer frame, the vertical height of the gate plate is controlled by a lifting mechanism arranged on the outer frame, and an antenna is mounted at the top of the outer frame. An upper limiting sensor and a lower limiting sensor are installed on the inner side of the outer frame. Photovoltaic power supply is adopted, so that the dependence on commercial power is reduced, and the energy consumption and the operation cost are reduced; remote control: remote control is realized through a 4G network, the operation is simple and convenient, and the management efficiency is improved; a radar liquid level meter is connected, the height of the gate is automatically adjusted according to the water level, the irrigation efficiency is improved, and water resources are saved; the circuit board displays the gate height, the battery voltage and the photovoltaic voltage in real time, and monitoring and maintenance are facilitated.

This utility model discloses a substation emergency backup power supply system and a substation power outage control system. The substation emergency backup power supply system includes: a main control circuit, an AC-to-DC circuit, an auxiliary power supply, a battery module, a constant current charging circuit, a battery voltage acquisition circuit, a battery switching circuit, and a motor control circuit. The output terminal of the main control circuit is connected to the input terminal of the motor control circuit, enabling it to send control signals to the motor control circuit. The motor control circuit is connected to a drive mechanism, which is connected to the substation high-voltage switch, enabling it to control the switching action of the substation high-voltage switch. The substation emergency backup power supply system and substation power outage control system proposed in this utility model can improve the safety and intelligence of substation power outage shutdown.

This invention discloses an adaptive sleep method and system for LoRa terminals used in dam monitoring, based on multi-dimensional environmental feature perception and hardware collaboration. The core of the method is as follows: after waking the terminal via RTC, it collects multi-dimensional parameters such as water level, ambient temperature, battery voltage, and channel signal-to-noise ratio, and calculates the dynamically adaptive sleep duration based on the weighted multi-dimensional features; it achieves active wireless channel avoidance through LoRa CAD channel listening, abandoning invalid transmissions and extending the sleep duration in harsh environments; it physically cuts off the power supply to the sensors during non-operation periods through a hardware-level anti-interference power gating circuit, eliminating static leakage; and it sets up a fallback mechanism for abnormal fault diagnosis to avoid unnecessary power consumption under extreme conditions. This invention completely solves the core contradiction between "long battery life" and "high responsiveness" in existing dam monitoring terminals, improving battery life performance.

A vehicle includes an engine, an intake manifold, a starter motor, a battery, and a control apparatus. The intake manifold is coupled to the engine. The starter motor is configured to start up the engine. The battery is configured to drive the starter motor. The control apparatus includes one or more processors, and one or more memories coupled to the one or more processors. The one or more processors are configured to execute idle reduction control, and execute, during execution of the idle reduction control and before cancelling the idle reduction control, adjustment control of adjusting an internal pressure of the intake manifold and causing the internal pressure of the intake manifold to be lower as a voltage of the battery is lower.

The present application relates to methods and apparatus for optimizing fast battery charging. In the described example of a method and apparatus for fast charging a battery with optimized charging, a system (400) includes a battery charger (420) for applying a voltage to a rechargeable battery (430), and a controller (422) coupled to the battery charger (420) and monitoring at least one of a battery voltage, a battery temperature, and a current flowing into the battery (430). The system (400) is configured to apply a charging current from the battery charger (420) by calculating an open circuit cell anode voltage and anode resistance of the battery (430) and determining a charging current. In an additional arrangement, lithium ion plating is prevented by the charging current.

A device and method for an integrated photovoltaic power module. A module include a photovoltaic cell, a rechargeable battery, an alternating current electrical port, and a microinverter. The microinverter has a first link at a first voltage coupled to the photovoltaic cell, a second link at a second voltage, and a boost converter converting power between the first link and the second link. The module includes a DC-to-AC power converter exchanging electrical power between the second link and the alternating current electrical port at an AC voltage. The module has a battery voltage converter with a battery port electrically connected to the rechargeable battery and a first link port connected to the first link and converting between a voltage of the rechargeable battery and a voltage of the first link.

The invention discloses a single-stage multi-port converter DC side current ripple suppression method and device and a storage medium, and the method comprises the steps: obtaining an initial three-phase sinusoidal modulation wave according to the AC side three-phase voltage and current of a converter; obtaining a battery current control value according to the DC side photovoltaic voltage and current; obtaining an asymmetric carrier wave according to the DC side photovoltaic voltage and the energy storage battery voltage; according to the initial three-phase sinusoidal modulation wave and the asymmetric carrier wave, a battery current actual value is obtained, iteration is carried out according to an error between the actual value and a control value, and a zero-sequence component when the error is smaller than an error tolerance is obtained; injecting the zero-sequence component into the initial three-phase sinusoidal modulation wave to obtain an improved modulation wave; and intersecting the improved modulation wave with the asymmetric carrier wave to obtain a PWM driving signal of the converter. According to the invention, direct-current side current ripple suppression and power distribution between optical storage are realized through a zero-sequence component injection method, and the method has the characteristics of remarkable ripple suppression effect, low implementation cost and the like.

The invention relates to an energy storage battery anomaly detection method, and the method comprises the steps: obtaining the voltage sequence data of an energy storage battery cluster, segmenting each battery voltage sequence in a sliding window manner to obtain window data, calculating the sequence correlation and the prior correlation of the window data through a pre-constructed Angle-Transform model to obtain a correlation difference, and determining the anomaly of the energy storage battery cluster according to the correlation difference. Establishing a loss function based on the association difference and the reconstruction error, performing adversarial alternate training on the model according to the loss function to obtain a target reconstruction error, obtaining an abnormal score of each battery according to the target reconstruction error, sorting the abnormal scores of all batteries, and determining an abnormal judgment threshold by using an inflection point detection method; and determining the abnormal condition of the battery according to the abnormal judgment threshold value and the abnormal score of each battery. Through the method and the device, the problem of inaccurate energy storage battery anomaly detection is solved, the anomaly score judgment is only based on the target reconstruction error, the method and the device are suitable for anomaly detection of the energy storage battery, and missing report and false report are reduced.

The application relates to the technical field of battery management, in particular to a method and device for early warning of internal short circuit of a lithium iron phosphate battery of a vehicle, wherein the method comprises the following steps: acquiring charging battery data of the lithium iron phosphate battery of the vehicle; acquiring a battery voltage curve of the lithium iron phosphate battery according to the charging battery data, and obtaining a plurality of feature points according to a plurality of curvature maximum points of the battery voltage curve; acquiring change information between the plurality of feature points, and controlling the vehicle to give a warning prompt when the change information reaches a preset internal short circuit early warning condition. According to the application, the plurality of feature points can be obtained according to the plurality of curvature maximum points of the battery voltage curve of the lithium iron phosphate battery, and the vehicle can be controlled to give a warning prompt when the change information between the plurality of feature points reaches the preset internal short circuit early warning condition, so that the accuracy of the calculation result is effectively improved, and the robustness and real-time performance of the internal short circuit early warning of the battery are improved.

This invention discloses an adaptive charging method for nickel-metal hydride batteries based on pulse modulation. By simultaneously sampling the temperature at multiple characteristic locations on the battery surface and calculating the average temperature, thermal field standard deviation, and maximum battery temperature, a comprehensive quantitative perception of the overall and local thermal state of the battery is achieved, overcoming the limitations of single-point temperature measurement and accurately identifying local thermal risks. By comparing the thermal field standard deviation with a thermal field imbalance threshold and switching the charging control mode based on the comparison result, combined with a differentiated duty cycle adjustment strategy matched to the charging control mode, adaptive control of charging parameters is achieved, balancing charging efficiency when the thermal field is uniform and suppressing local hot spots when the thermal field is unbalanced. By simultaneously monitoring the real-time battery voltage, maximum battery temperature, and cumulative charging time, and immediately stopping pulse charging when a set threshold is reached, a triple safety protection mechanism is constructed, mitigating overcharging and overheating risks from multiple dimensions and significantly improving the safety and reliability of the charging process.

A system and method for characterizing a battery of a battery power system and a battery power system are provided. The system for characterizing a battery of a battery power system includes a sensor array, a processor, and a memory. The sensor array measures a temperature-specific battery voltage and a battery current of the battery as battery parameters. The processor executes instructions from the memory to provide or create a baseline open circuit voltage to state of charge (OCV-SOC) characteristic relationship during a series of charge and discharge modes of the battery. After creating or accessing the baseline OCV-SOC characteristic relationship, the processor determines whether the battery is in an open mode during which the battery is not connected to a load. In an open mode, the battery parameters are measured via the sensor array. An adjusted OCV-SOC characteristic relationship is created by adjusting the SOC amount of the baseline OCV-SOC characteristic relationship using the battery parameters. The battery is controlled using the adjusted OCV-SOC characteristic relationship.

The invention relates to a lithium ion energy storage prefabricated cabin risk toughness assessment method based on a fuzzy Bayesian network model. According to the method, real-time operation data, including risk factors such as battery voltage, current, temperature, available capacity, dew point temperature, dust concentration, air velocity and altitude, of the energy storage prefabricated cabin and equipment state data of a battery management system, a fire prevention system and a gas monitoring system are collected. Through processing and calculation of the data, key risk indexes related to the fire risk are determined, and the fault probability of each system is calculated. A risk level of a risk index is converted into a fuzzy number by using a fuzzy set theory, and then the fuzzy number is converted into a prior probability through a left-right fuzzy sorting method. In combination with historical statistical data of the energy storage prefabricated cabin, a Bayesian network total probability formula is used to calculate the probability of fire occurrence, and a reverse reasoning mechanism is used to identify a risk factor which is most likely to cause the fire. And quantitative and dynamic evaluation of the fire risk of the energy storage prefabricated cabin is realized.