1324 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 present invention relates to the technical field of batteries, and discloses a battery and a battery pack, the battery comprises: a battery cell comprising a battery cell body and a tab part extending from the battery cell body; the pole assembly is welded with the tab part to form a first welding mark area, and a non-welding area is formed on the part, without the welding mark, of the tab part; the tab part comprises a plurality of tab layers which are stacked in the z direction, the surface roughness of the tab layers is R, the orthographic projection area of the first welding printing area on the tab part in the z direction is S, the thickness of the non-welding area in the z direction is T1, the thickness of the first welding printing area is T2, and the formula that (T2 * R) / (T1 * S) is larger than or equal to 1.4 * 10 <-6 > and smaller than or equal to 5.4 * 10 <-5 > is met. According to the invention, the over-current capability between the pole assembly and the tab part is ensured, the charging and discharging rate of the battery is improved, the voltage jump of the battery is avoided, the reliability of the battery is ensured, the welding strength of the tab part and the pole assembly is improved, the difficulty degree of the welding process is reduced, and the welding efficiency is ensured.

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 present invention discloses a voltage-configurable rechargeable battery device and charging terminal and charging station, wherein the voltage-configurable rechargeable battery device comprises a rechargeable battery, a battery voltage management circuit, and a battery capacity acquisition circuit; the rechargeable battery is electrically connected to a charging terminal; the battery voltage management circuit comprises a boost / buck management circuit; the battery capacity acquisition circuit is connected to the battery voltage management circuit; the rechargeable battery can realize discharge curve following according to the current capacity via the battery voltage management circuit. The present invention can ensure basically consistence of the actual power level and the displayed power level, and improve users' experience.

The invention discloses a multi-rotor trajectory tracking optimization method based on MLP acceleration estimation and reinforcement learning, and relates to the technical field of flight control, and the method comprises the steps: receiving a target position of an unmanned aerial vehicle, synthesizing a man-machine position, speed, attitude, relative position error and a current battery voltage value into an observation vector, inputting the observation vector into a reinforcement learning model, and carrying out the reasoning, outputting the planned reference acceleration to a controller; the controller obtains an expected attitude and an expected thrust of the unmanned aerial vehicle according to a kinematics formula; and adjusting an optimization algorithm of control parameters in real time through the thrust-accelerator compensation network model, calculating a corresponding accelerator value, and solving an optimal bottom layer control instruction. According to the method, the target acceleration generated by reinforcement learning is taken as a core control quantity, high-performance flight control is realized through a hierarchical control strategy, and the system can still keep excellent trajectory tracking performance and control stability even under the condition that obvious battery voltage fluctuation exists.

The invention relates to the technical field of battery management, in particular to an intelligent charging adjustment method and system based on dynamic monitoring, and the method comprises the steps: determining a tested energy storage battery, determining a target battery based on a charging adjustment instruction, carrying out the feature extraction of a plurality of historical charging data and the previous full capacitance, and obtaining a charging emergency coefficient and a battery aging coefficient; a humidity sensor and a temperature sensor are used for obtaining current humidity and current temperature respectively, particle swarm simulation is carried out on a charging emergency coefficient, a battery aging coefficient, a constant current curve set, a constant voltage curve set, a switching curve set, the current humidity and the current temperature, and target constant current, target constant voltage and a target switching threshold value are obtained; and if the target battery voltage is greater than or equal to the target switching threshold, performing charging adjustment on the target battery according to the target constant voltage and the target switching threshold to obtain a final battery, and completing intelligent charging adjustment. The safety and stability of the charging process can be improved, and the service life of the battery is prolonged.

A battery management device according to one embodiment of the present invention includes: a profile acquisition unit configured to acquire a battery profile and a differential profile based on the voltage and capacity of the battery; and a control unit configured to generate a comparative full-cell profile and a comparative differential profile based on a preset reference positive electrode profile and a preset reference negative electrode profile, adjust the reference positive electrode profile and the reference negative electrode profile so that the comparative full-cell profile and the comparative differential profile correspond to the battery profile and the differential profile, respectively, and determine the adjusted positive electrode profile and adjusted negative electrode profile as the positive electrode profile and the negative electrode profile of the battery, respectively.

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.

The present invention provides a server for diagnosing a defect in a battery, the server including a server communication unit configured to receive battery data including at least one of a battery voltage, a battery current, and a battery temperature, which is a temperature of the battery, from a battery management system (BMS); a server storage unit configured to store a plurality of internal resistance values of the battery calculated based on the battery data at each diagnosis time point for diagnosing the defect in the battery; and a server control unit configured to extract a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on a diagnosis time point, calculate a moving average, compare an internal resistance value with an upper band threshold, and a lower band threshold, and diagnose the defect in the battery.

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.

A low battery voltage protection method for a microcontroller system and a microcontroller system using the same are provided. The low battery protection method and the microcontroller system are used to prevent continuous battery drain by setting time thresholds and a count threshold. In an embodiment, when a low-voltage power-on reset voltage is not exceeded within a first preset time, the microcontroller system is forced to enter a sleep mode to prevent power consumption by an analog block. In another embodiment, when the low-voltage power-on reset voltage is exceeded, but a reset count of the microcontroller system exceeds a preset value within a second preset time, the microcontroller system is also forced to enter the sleep mode to prevent a digital block from continuously loading data, which could lead to battery failure.

The utility model provides a back electromotive force electric energy recovery circuit of an unmanned aerial vehicle and the unmanned aerial vehicle. The multiple battery voltages are combined through the combining output circuit to supply power to the load, when back electromotive force exists due to deceleration of the unmanned aerial vehicle, the multiple battery voltages are detected through the comparison circuit, and if the back electromotive force voltage is larger than the voltage of each battery, at least one reverse charging circuit is opened to charge the battery. According to the embodiment, when the multiple batteries supply power to the unmanned aerial vehicle, mutual charging between the batteries can be prevented, counter electromotive force electric energy generated when the motor slows down can be absorbed through the batteries, uninterruptible power supply of the unmanned aerial vehicle can be achieved through hot plugging of the batteries when the unmanned aerial vehicle is in a standby state, and the unmanned aerial vehicle is convenient to use. The time for starting up, shutdown and initialization of the unmanned aerial vehicle due to battery replacement is shortened, and the working efficiency of the unmanned aerial vehicle is improved.

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 method for carrying out overcharge protection by utilizing a voltage change rate, which comprises the steps of S1, monitoring the voltage change rate in real time, S2, carrying out data analysis processing and early warning, S3, processing an abnormal condition, S4, carrying out settlement comparison on a recorded result and the like, so as to obtain an abnormal result of the voltage change rate of a battery. According to the method, by monitoring the voltage change rate of the battery in real time, the abnormal performance of the battery can be found in time, the real-time performance and the accuracy of battery testing are improved, the safety and the reliability of the battery can be guaranteed, early warning can be carried out on the overcharge condition of the battery, and potential safety hazards caused by overcharge and overdischarge of the battery due to personnel errors are prevented; and meanwhile, the service life of the battery is ensured, and the abnormity of the voltage change rate can be found in time, so that the battery failure is effectively prevented, the use safety and reliability of the battery are improved, and the safety of testers is also ensured.

The invention belongs to the field of batteries, and provides a multi-source parameter fusion battery system intelligent grading early warning method and device in order to solve the problem that an early warning method is poor in dynamic working condition adaptability and difficult to adapt to parameter drift caused by battery aging. The multi-source parameter fusion battery system intelligent grading early warning method comprises the following steps: preprocessing multi-source parameter data in a battery pack operation process to obtain battery operation time sequence data; processing the battery operation time sequence data by using an attention-enhanced Mamba model to obtain a battery voltage predicted value; comparing the battery voltage predicted value with a real voltage value to generate error information; and according to comparison between the error information and preset threshold conditions of different early warning levels, corresponding early warning level signals are triggered, and accurate prediction and intelligent early warning of voltage abnormity of the battery pack can be realized.

The present invention relates to the technical field of electric vehicle charging. Provided are a method for performing supplementary charging on a low-voltage storage battery of a vehicle, and a related device. The method comprises: after a vehicle is powered off, detecting whether a CAN of the vehicle is in a sleep state; when the CAN network is not in the sleep state, determining whether the vehicle meets a low-voltage supplementary charging trigger condition, wherein the low-voltage supplementary charging trigger condition comprises the voltage of a storage battery of the vehicle being less than a preset voltage and the number of instances of supplementary charging in a single power-off cycle not exceeding a preset number of instances; when the CAN is in the sleep state, acquiring a sleep time, so as to wake up the sleeping CAN when the sleep time satisfies a wake-up time; and when the vehicle meets the low-voltage supplementary charging trigger condition or the CAN in the sleep state is woken up, sending a low-voltage supplementary charging request, so as to perform supplementary charging on the vehicle.

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 discloses a pulse simulation test method and test control equipment for an electric vehicle battery, and relates to the technical field of electric vehicle battery test. In the method, a test control device firstly identifies voltage extreme points caused by inherent ripples of a charging pile, and generates an event sequence based on the extreme points. And then, the test control equipment determines the type of a synchronous trigger point from a preset trigger strategy table according to the state of charge of the battery, and executes a pulse pull flow operation when the type of the extreme point is consistent with the type of the trigger point. By collecting battery voltage and current response data, the test control equipment calculates characteristic parameters and generates a performance evaluation report. According to the method, the coupling degree of the pulse frequency and the ripple frequency of the charging pile can be reduced without adding a physical isolation module, and meanwhile, the specific voltage ripple of the charging pile is reserved as an evaluation basis, so that the microcosmic electrochemical damage test accuracy of the electric vehicle battery is improved.

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 relates to the technical field of output control, in particular to a constant power control method, device and equipment based on COT and a storage medium, according to the method, fixed turn-on time is combined with dynamic turn-off time adjustment, the conciseness of COT control is reserved, accurate control over output power is achieved, and the control efficiency is improved. The influence of interference factors such as battery voltage drop and load abrupt change on constant power output can be effectively counteracted; specifically, a multi-path output synchronous opening design is adopted, and unified turn-off time adjustment logic is combined, namely, the turn-off time of a (k + 1) th period is calculated according to the total duration of a target period, so that an asynchronous turn-off condition caused by parameter differences of all channels is avoided, and the voltage rise deviation generated by load changes of a later turn-off channel is reduced; real-time output voltage and load resistance are respectively sampled in one period, battery voltage fluctuation and load change are monitored in real time, and error accumulation caused by the fact that a measured value in the current period is extended to the next period to be adjusted is avoided.

The invention belongs to the technical field of optical storage operation control, and particularly relates to an operation mode seamless switching control method of a photovoltaic-energy storage system, which comprises the following steps of: for an optical storage system comprising an energy storage system and a photovoltaic system, performing seamless switching on the operation modes of the photovoltaic-energy storage system; obtaining a direct current bus voltage, a photovoltaic output voltage and current, an energy storage battery voltage and current, an LC filter inductance current and a grid-connected point voltage and current in the current optical storage system; aiming at an energy storage system, constructing a switching mechanism based on photovoltaic voltage feedforward; aiming at a photovoltaic system, constructing a dynamic control strategy based on photovoltaic power feed-forward compensation; based on a switching mechanism and a dynamic control strategy, network construction control is carried out by combining an inverter virtual synchronous generator control technology, and stable operation of the optical storage system in strong power grid and weak power grid environments is realized. The system is suitable for an optical storage system, can cover various typical operation modes, and has high responsiveness and high stability.

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.