2680 results about "Battery charge" patented technology

An ID token wirelessly communicates a battery voltage to a vehicle gateway via short-range communication. A battery health may be determined based on the current battery voltage and one or more previous battery voltages associated with ID token. Replacement of the ID token may be initiated based on the battery health to avoid communication failures by the ID token due to insufficient battery charge.

The invention provides a lithium battery SOH estimation method based on a time sequence diagram neural network under physical constraints. The method comprises the following steps: collecting battery charge-discharge cycle data; time-related statistical characteristics and IC curve characteristics are extracted from the battery charge-discharge cycle data, and analysis characteristics are obtained after PCC analysis; calculating a time sequence distance between analysis features based on a sliding window and multi-channel collaborative dynamic time warping, and constructing a graph structure; constructing a time sequence diagram neural network, firstly extracting spatial features through diagram convolution, and then modeling a degradation law through time convolution to obtain a preliminary SOH predicted value; defining a physical residual error loss and a monotonicity regular term, and performing weighted combination on the physical residual error loss and the monotonicity regular term and data fitting loss to construct a joint optimization objective function; based on the optimization target, a final constrained SOH predicted value is obtained through a back propagation training model; therefore, in combination with a physical information constraint mechanism, high-precision and physically consistent SOH prediction is realized.

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.

A battery charging system includes a charging rack comprising multiple receptacle, multiple battery assemblies. Each of the battery assemblies includes a housing having a handle, rechargeable battery cells disposed within the housing, and a mating feature protruding away from the housing, wherein the mating feature is configured to selectively connect the battery assembly with the receptacle of the charging rack and includes multiple ports electrically connected to the battery cells and configured receive power from the charging rack to charge the battery cells, and wherein the handle comprises a release button configured to selectively disengage the battery assembly from the receptacle of the charging rack.

The invention discloses a lithium battery health state estimation method based on transfer learning, and the method comprises the steps: firstly carrying out the normalization and time sequence reconstruction of a battery charging voltage-capacity curve, and constructing a unified input sequence; extracting long-time-sequence degradation characteristics based on a Mama network, and completing SOH regression prediction through a two-stage full connection layer; in the cross-domain adaptation stage, in combination with an alignment strategy of dynamic time warping and weighted maximum mean difference, time sequence matching and feature distribution alignment in the degradation stage are realized; meanwhile, on the basis of a sample weighting mechanism of a Wasserstein distance, the effectiveness of migrating source domain knowledge to a target domain is improved; through a two-stage strategy of source domain pre-training and source-target joint training, a relatively low prediction error and a relatively high fitting degree can be kept under the condition that a target domain is not labeled; the method shows good generalization ability and robustness under different battery types and different working conditions, and can provide reference for health management of the electric vehicle.

The invention relates to the technical field of micro-grid dispatching, and particularly provides an intelligent dispatching method and system for a photovoltaic-storage-diesel micro-grid, and the method comprises the steps: obtaining the operation data of an energy storage battery, the operation data of a diesel generator, and the global operation data of the micro-grid; evaluating the power response capability of the energy storage battery according to the operation data of the energy storage battery, and evaluating the quick response capability of the diesel generator according to the operation data of the diesel generator; analyzing the stability risk level of the micro-grid according to the global operation data, the power response capability and the quick response capability of the micro-grid; adjusting scheduling optimization target emphasis according to the stability risk level; emphatically acquiring an energy storage battery charging and discharging instruction, a diesel generator starting and stopping instruction and an output instruction according to the adjusted scheduling optimization target, and executing all the acquired instructions; according to the method, the problem that the system stability is sacrificed due to blind pursuit of cost minimization in a traditional strategy can be avoided.

The present invention relates to the technical field of batteries, and provides a battery cover plate, a battery and a battery pack, the battery cover plate comprises: a cover plate body provided with a through hole; the sealing plate is arranged at the through hole, and the sealing plate is in sealing connection with the through hole; the boss is arranged on the outer side of the sealing plate in the first direction, the boss extends out of the through hole in the first direction, a plurality of convex ribs with closed outlines are integrally formed on the end face of the side, away from the cover plate body, of the boss, and the first direction is the thickness direction of the cover plate body; the surface area of the outer surface of the boss is increased through the existence of the convex ribs, meanwhile, the heat dissipation area of the battery cover plate is greatly increased, heat generated by a system can be rapidly conducted and dissipated in the charging and discharging process of the battery, the working temperature of the battery is effectively reduced, the battery can stably adapt to the high-rate rapid charging technical scheme, and in addition, the service life of the battery cover plate is prolonged. Through the design, the surface of the boss can be coated with the structural adhesive, and the bonding area of the structural adhesive and the boss is remarkably increased.

In an approach to a state of health for grid applications, a system includes one or more battery energy storage systems having a plurality of batteries; energy sources; power distribution systems; and computing devices. The computing devices are configured to: for each of the battery energy storage systems: receive battery parameters for each of the batteries from the battery energy storage systems; determine a lithium plating state, a solid electrolyte interface (SEI) thickness, and a dendrite length for each of the plurality of batteries; determine a battery state of health (SOH) for each of the batteries based on at least one of the lithium plating state, the SEI thickness, and the dendrite length; determine a battery charge profile to mitigate aging for each of batteries based on the SOH; and send updated battery parameters and control thresholds for each of batteries to each of the battery energy storage systems.

The invention provides a dynamic power adaptive charging control system and method based on a W algorithm, and relates to the technical field of electric two-wheeled vehicle charging control. The system comprises a battery state sensing module, a charging power standard calculation module, a regulation and control model construction module, a model dynamic optimization module and a deviation early warning and regulation and control module. The battery state sensing module generates battery charging basic data; the charging power standard calculation module calculates a charging operation power standard value; the regulation and control model construction module generates an initial power regulation and control curve; the model dynamic optimization module calculates a self-adaptive charging power regulation and control curve; and the deviation early warning and regulation module realizes self-adaptive regulation of the charging power of the electric two-wheeled vehicle. According to the method, the power grid adaptability correction model is constructed and the regional differentiation parameters are introduced, so that power grid fluctuation is flexibly coped, wide-voltage stable operation is guaranteed, and the adaptability, the safety and the intelligent level of the electric two-wheeled vehicle charging system are comprehensively enhanced.

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

The invention relates to the technical field of intelligent automobiles, in particular to a battery performance test method and system for an intelligent automobile, and the method comprises the steps: obtaining the operation data of each single battery of the intelligent automobile under the current driving working condition and the working condition statistical data of the automobile, and constructing an input feature set, standardizing the input feature set, and inputting the standardized input feature set into a battery performance evaluation model to obtain key performance indexes of the single battery; dynamically adjusting a battery charging and discharging control strategy according to the key performance index and a real-time load demand under the current driving condition, verifying the accuracy of the key performance index by comparing the voltage fluctuation amplitude and the temperature change rate of the battery before and after adjustment, comparing with a preset safety threshold value, and if the threshold value range is exceeded, determining that the battery is in a charging state. If yes, generating corresponding performance early warning information; the method can adapt to complex and changeable driving working conditions of the intelligent automobile, and the precision and the real-time performance of battery performance evaluation are remarkably improved.

The invention discloses an intelligent control method and system for a solar street lamp, and particularly relates to the technical field of intelligent control. The method comprises the following steps: collecting photovoltaic power generation data and battery charging and discharging data of a solar street lamp node, analyzing difference characteristics of photovoltaic power generation capacity of the solar street lamp node in space and fluctuation characteristics of a battery energy storage state in time, and outputting space difference characteristic data and time fluctuation characteristic data; power generation space imbalance evaluation data and energy storage time abrupt change evaluation data are output by evaluating power generation imbalance distribution characteristics and energy storage state abrupt change characteristics caused by dynamic shielding; a local energy link imbalance prediction model is constructed, energy link imbalance prediction data of solar street lamp nodes are output, power distribution and brightness control strategies of solar street lamps are dynamically adjusted, and intelligent sensing and regulation of energy link instability under local shielding are achieved. And the operation stability and the energy-saving performance of the whole illumination system of the solar street lamp group are ensured.

A system detects degradation of battery health due to fast-charging and controls charging of the battery and / or provides indications of battery health while fast-charging. The system includes remove a battery charging circuit that controls a charging voltage waveform to supply charging current to a battery and a detection circuit that monitors a rate of change of the charging current and controls the charging voltage waveform responsive to an output of the detection circuit.

1. The name of the design product: the main body of the charger. 2. The use of the design product: the product as a whole is used to charge the battery, and the part claimed for protection is the main body of the charger, which is used to protect the internal components and play a decorative role. 3. The design points of the design product: the shape of the part drawn in solid lines. 4. The picture or photo that best indicates the design points: Figure 1. 5. Other circumstances that need to be explained: in each view, the part drawn in solid lines is the part claimed for protection, and the part drawn in dashed lines is not claimed for protection.

The invention discloses a new energy charging pile remote control method considering a battery health state. The method comprises the following steps of obtaining battery full life cycle data, charging pile real-time working condition data and charging area power grid dynamic data, and performing preprocessing to generate battery health baseline data, pile body operation reference data and power grid dispatching reference data; extracting current health state parameters of the battery based on the health baseline data of the battery, calculating a charging adaptation coefficient in combination with the operation reference data of the pile body, analyzing the redundant capacity of the power grid, and constructing a charging control decision model; outputting an initial charging parameter combination based on the charging control decision model, performing health protection correction, and generating a basic remote control instruction; and issuing the basic remote control instruction to the target charging pile to calculate an instruction execution deviation degree, and performing dynamic iterative optimization to generate a new energy charging pile remote control scheme. According to the invention, collaborative optimization of safety and high efficiency of new energy vehicle charging and battery charging protection can be realized.

1. The name of the design product: the guide rail of the charger. 2. The use of the design product: the product as a whole is used for charging the battery, and the claimed part is the guide rail for guiding the battery to engage with the charger. 3. The design points of the design product: the shape of the part drawn in solid line. 4. The picture or photo that best shows the design points: perspective view 1. 5. Other circumstances that need to be explained: in each view, the part drawn in solid line is the claimed part, and the part drawn in dashed line is not claimed.

The invention relates to a battery charging optimization method and device, a vehicle and a storage medium. The method comprises the steps of obtaining a current battery health value, a battery nominal capacity, a battery theoretical cut-off charging voltage and a current user endurance demand based on a battery charging demand; determining a target charging electric quantity based on the current user endurance demand, the battery nominal capacity and the current battery health value, and determining a target charging cut-off voltage based on the battery theoretical cut-off charging voltage; and generating a charging optimization strategy according to the target charging electric quantity and the target charging cut-off voltage, and charging the battery by using the charging optimization strategy. Therefore, the charging amount and the charging cut-off voltage are properly reduced on the basis of the battery health degree, the battery temperature and the vehicle using requirement of a user, and the problem that the cycle life of the battery is seriously shortened due to the fact that the battery is charged according to fixed charging parameters and the actual aging state of the battery is not considered in the prior art is solved; and the battery capacity fading rate can be reduced on the premise of meeting the vehicle use requirement of a user.

The invention discloses a battery state-of-charge detection method based on deep learning and ultrasonic feature fusion. The method comprises the following steps: collecting and preprocessing battery ultrasonic signals and battery electrical parameters; extracting an ultrasonic amplitude; extracting and fusing the characteristics of the battery voltage, the surface temperature, the ultrasonic amplitude and the phase difference; the method comprises the following steps of: optimizing parameter values of a BiTCN-BiLSTM-Multi-Head Attention network on the basis of a WAA weighted average optimization algorithm, extracting basic characteristics related to the SOC of the battery in a characteristic matrix on the basis of a bidirectional time convolution network BiTCN, extracting long-term information related to the SOC of the battery in the basic characteristics on the basis of a BiLSTM network, extracting important characteristics related to the SOC of the battery in the long-term information on the basis of a Multi-Head Attention network, and calculating the SOC of the battery according to the extracted important characteristics. And outputting a predicted value of the SOC of the battery through the full connection layer. According to the invention, the estimation precision of the battery SOC can be improved.

1. The name of the design product: the charging terminal of the charger. 2. The use of the design product: the product as a whole is used for charging the battery, and the part claimed for protection is the charging terminal part for charging. 3. The design points of the design product: the shape of the part drawn in solid line. 4. The picture or photo that best shows the design points: perspective view 1. 5. Other circumstances that need to be explained: in each view, the part drawn in solid line is the part claimed for protection, and the part drawn in dashed line is not claimed for protection.

The invention provides an intelligent charging system and method based on illumination intensity adaptive adjustment. The intelligent charging system and method are applied to a photovoltaic energy storage system comprising a photovoltaic cell, a DC-DC converter, a storage battery charging mode control module and a storage battery. The method comprises the following steps: firstly, acquiring current illumination intensity, an incident light angle and a working environment temperature, and sending the current illumination intensity, the incident light angle and the working environment temperature to a photovoltaic cell and storage battery charging mode control module; the photovoltaic cell outputs corresponding voltage and current based on the parameters and a temperature compensation mechanism; and the storage battery charging mode control module converts the output of the photovoltaic battery into charging voltage and current for the storage battery, and dynamically determines a constant-voltage or constant-current charging mode in combination with the illumination intensity, the environment temperature, the incident light angle and the charging parameters, so that the self-adaptive charging of the storage battery is realized. Through multi-parameter cooperative adjustment, the charging mode is accurately matched with the environment condition and the storage battery state, and the charging efficiency and the system stability can be improved.

The invention provides a battery state-of-charge estimation method and system based on a physical gating neural network, and the method comprises the steps: obtaining battery operation data, and inputting the data to a data drive estimation module to obtain a preliminary SOC estimation value; meanwhile, the physical correction module performs integration on the battery operation data to obtain a physical estimation value, and generates a correction estimation value under physical constraint; calculating confidence through a confidence gating module to perform weighted fusion on the initial estimation value and the corrected estimation value, and outputting a final state of charge estimation result; and determining an optimal hyper-parameter through K-fold cross validation and completing network training to obtain a trained physical gating neural network, and predicting a state-of-charge estimation value of the battery based on the trained physical gating neural network. According to the method, high-precision and low-error SOC estimation can be realized under a complex multi-cycle charging and discharging working condition, and the stability and the reliability of an estimation result are remarkably improved.

The invention discloses a battery charging and discharging power self-regulation control circuit, which relates to the technical field of battery control, and comprises a power supply module, a micro-control module, a voltage sampling and comparison module, a battery charging and discharging power self-regulation control module, a battery charging and discharging power self-regulation control module, a battery charging and discharging power self-regulation control module and a battery charging and discharging power self-regulation control module, the power regulation module compensates the direct-current electric energy, the battery module stores energy, the power regulation module and the direct-current electric energy are superposed and supply power to the battery module, during the discharging period, according to the voltage comparison condition, the power regulation module carries out voltage compensation processing on the battery module, and the battery module directly supplies power to the discharging module; and the power regulation module performs voltage balance control on the battery module. The battery charging and discharging power self-adjusting control circuit can prolong the service life of the battery, improve the charging and discharging efficiency, reduce the electric energy loss of the power adjusting module, improve the energy utilization rate and provide higher charging voltage.

Disclosed in the present invention are a photovoltaic air conditioning system, and a control method and control apparatus therefor. The control method comprises: obtaining air conditioner load prediction result data on the basis of known air conditioner load data and an established air conditioner load prediction model; obtaining photovoltaic power generation prediction result data on the basis of known photovoltaic data and an established photovoltaic power generation prediction model; obtaining power grid load prediction result data on the basis of power grid data and an established power grid load prediction model; determining a first energy storage battery charging and discharging strategy on the basis of the air conditioner load prediction result data, the photovoltaic power generation prediction result data and the power grid load prediction result data; and determining a second energy storage battery charging and discharging strategy on the basis of the first energy storage battery charging and discharging strategy and a state-of-charge threshold adjustment strategy, and controlling the charging and discharging process of an energy storage battery assembly on the basis of the second energy storage battery charging and discharging strategy. The present invention can improve the efficient operation performance of a photovoltaic air conditioning system.

The invention relates to a lithium battery parameter identification method based on a physical information neural network, and belongs to the field of battery health and management. The method comprises the following steps: firstly, acquiring a data set, receiving battery charging data through a battery management system, then preprocessing the data, calculating label capacity through an ampere-hour integral method, and performing an experiment by using an electrochemical workstation to obtain specific electrochemical parameter data. The method comprises the steps that firstly, a single-particle model with an electrolyte is constructed, then an encoder is used for extracting multi-scale time characteristics of battery data, a decoder is introduced to accurately capture key information of the battery data, and finally, the single-particle model with the electrolyte is fused with a whole neural network model to construct a physical information neural network, so that the identification precision and efficiency of the whole framework on internal parameters of the lithium battery are improved. Experimental results show that the method can effectively identify six battery internal key parameters including a solid phase diffusion coefficient, electrical resistivity of an EI film, liquid phase lithium ion concentration, an electrolyte diffusion coefficient, effective electrolyte conductivity and transfer number.

The invention relates to the technical field of electrochemical energy storage systems, and discloses an electrochemical energy storage system battery charging effect evaluation method, which comprises the following steps: acquiring energy storage system operation data and battery charging records, extracting time sequence characteristics, equipment state characteristics and charging parameter characteristics, and calculating the charging effect of an electrochemical energy storage system battery. Constructing a multi-dimensional feature vector and generating an initial charging effect feature library; the evaluation model is dynamically adjusted based on feature library feedback, potential effect features are identified through mode clustering analysis, feature priorities are optimized, and model parameters are updated; and in combination with system configuration information and target model parameters, determining an optimal power compensation effect evaluation result by adopting a hierarchical disassembly and classification statistical method. According to the method, through multi-dimensional feature fusion, dynamic model optimization and refined statistical analysis, the accuracy and adaptability of electricity supplement effect evaluation are remarkably improved, and a scientific basis is provided for efficient operation and maintenance of the electrochemical energy storage system.

The disclosure relates to an apparatus for charging or discharging including a case, a charging or discharging module unit and an air treatment unit provided inside the case, an equipment temperature sensor located in the case and sensing an equipment temperature, a module hole formed by communicating with the outside, and a controller charging or discharging, where the controller is configured to discharge at least a portion of the air discharged from the air treatment unit to the outside of the case through the module hole based on usage current of the charging or discharging module unit and the equipment temperature, a battery charging or discharging system including the same, and a control method thereof.

The invention relates to the technical field of electrochemistry and energy storage, and discloses a battery life and charging efficiency equalization optimization method and system, and the method comprises the steps: extracting the capacity fading rate, internal resistance change trend and temperature sensitivity of a target battery; analyzing the real-time health state of the target battery and the battery chemical model, and establishing a dynamic reference charging curve of the target battery; defining a charging efficiency threshold value and an IDR safety limit value of the target battery; monitoring battery charging data in the charging process of the target battery in real time so as to analyze the current charging efficiency and the instantaneous attenuation rate of the target battery, and establishing a dual-target optimization function of the target battery; and the charging efficiency equalization parameters of the target battery are generated by using the dual-objective optimization function, and the charging efficiency equalization parameters comprise the optimized charging voltage, the optimized charging current and the optimized charging pulse interval, so that the service life of the battery can be prolonged, and the equalization optimization effect of the charging efficiency can be improved.

The invention provides a charging optimization method and device for a lithium battery, electronic equipment and a storage medium, and the method comprises the steps: dividing a charging process into two levels: a macroscopic planning level and a microscopic tracking level: a charging planning intelligent agent generates an optimal voltage reference trajectory on a long time scale, so as to optimize the service life of the battery and the overall charging efficiency; the charging tracking intelligent agent responds to instantaneous voltage, current and temperature changes in a short time scale, real-time voltage adjustment is achieved, and safety and accuracy of the charging process are ensured. By introducing a degradation mechanism reward item and a meta-reinforcement learning framework, collaborative optimization of the charging speed and the service life of the battery is realized, and the method also has a cross-task rapid adaptation capability, can efficiently migrate under different battery individuals, health states and environmental conditions, and has the advantages of high adaptability, high response speed, low hardware dependence and the like.

The invention discloses a charging control method and device based on a charging pile, electronic equipment and a storage medium. The method is applied to a charging pile group control system constructed based on a star flash network. The method comprises the following steps: receiving a charging request broadcasted through the star flash network; then distributing a first star flash channel to a vehicle battery management system of the target charging pile and the target vehicle battery based on the charging request; acquiring a battery charging parameter uploaded by a vehicle battery management system through the first star flash channel; based on group control information and battery charging parameters in the charging pile group control system, generating a charging strategy of a target vehicle battery; and finally performing charging control on the target vehicle battery based on the charging strategy. According to the method, the communication efficiency, the communication reliability and the communication safety of the charging pile can be improved through the satellite flash technology, intelligent dynamic response in a charging pile group control system is achieved, and the overall throughput of the charging station can be improved.

The invention relates to the technical field of flywheel and battery hybrid energy storage control, and discloses a quick power response and energy management method of a flywheel and electrochemical hybrid energy storage system. The method comprises the following steps of: acquiring flywheel rotating speed, kinetic energy allowance, battery end voltage and internal resistance in real time to form a state vector, performing consistency correction on an initial power decomposition instruction according to the state vector, and generating a final power instruction matched with unit real-time capability. Meanwhile, by monitoring the change trend of the flywheel kinetic energy and the battery charge state, a power decomposition coefficient is dynamically adjusted according to a preset coordination rule, and the power decomposition coefficient is fed back to an initial decomposition link to form closed-loop control. According to the method, accurate matching of the power instruction and the dynamic characteristics of the energy storage unit is realized, and the safety and accuracy of system response are improved; and through closed-loop trend adjustment, the long-acting adjustment capability and operation stability of the system are maintained.