187 results about "Dynamic charging" patented technology

The invention relates to the field of power battery energy management, in particular to a power battery pack charging and discharging efficiency dynamic optimization system and method, and the system comprises a central control unit, a multi-dimensional sensing module, a dynamic charging and discharging control module, a working condition-heat dissipation cooperation module, a parallel cell equalization module and an aging adaptation optimization module. The multi-dimensional sensing module is used for collecting basic parameters, polarization characteristics, parallel state, aging degree and environmental parameters of a battery pack, the dynamic charging and discharging control module is used for collecting data, the working condition-heat dissipation coordination module adopts a three-stage heat dissipation framework, and the parallel battery cell balancing module is used for balancing the battery pack through a dynamic current distribution and voltage active balancing double-coordination mechanism. The aging adaptation optimization module is used for grading and differentially optimizing charge and discharge parameters and heat dissipation strategies based on the aging degree of the battery cell, so that the problems of low charge and discharge efficiency, poor wide temperature range adaptability, weak parallel consistency, fast aging attenuation and multi-factor coupling deterioration of the power battery pack are solved.

The invention relates to the technical field of charging parking space guiding control, and particularly discloses a parking space charging reservation and intelligent guiding method, device, equipment and medium, and the method comprises the steps: obtaining vehicle battery state data and a user reservation time window through an Internet of Things terminal; synchronously acquiring charging pile state data, real-time traffic flow data and power grid load information in the parking lot; fusing the obtained multi-source heterogeneous data based on a federated learning framework, constructing a dynamic charging demand prediction model, and predicting charging pile occupancy rate distribution in a preset time period by using a space-time diagram convolutional network; through the combination of the dynamic charging demand prediction model and the space-time diagram convolutional network, the occupancy rate distribution of the charging piles is accurately predicted, the scheduling strategy of the charging piles is adjusted in real time, the problem of unreasonable resource allocation is avoided, and the waiting time of a user is shortened; the application of the quantum genetic algorithm optimizes the matching process of the charging pile through global optimal solution search, thereby ensuring the balance of the power grid load and the rationality of the charging strategy.

The invention relates to the technical field of energy storage battery control, in particular to a high-reliability low-attenuation energy storage battery management system based on intelligent control, and the system comprises a data collection module which is used for collecting battery temperature, environment temperature, SOC (state of charge), SOH (state of health) and external mechanical pressure information; the model construction module is used for constructing a battery attenuation risk dynamic coupling evaluation model and generating a battery safety and attenuation risk dynamic evaluation diagram; the self-adaptive adjustment module adopts a cross-dimension multi-stage cooperative control strategy algorithm, temperature compensation current control and SOH grading current limiting linkage are combined, and SOC dynamic charging optimization and mechanical pressure early warning are coupled; and the evaluation report module adjusts control parameters through a dynamic optimization algorithm, generates a battery health state evaluation report, synchronously uploads the battery health state evaluation report to a cloud database, and establishes a full-life-cycle battery attenuation risk file. Therefore, the problems that in the prior art, a risk assessment model is large in limitation, a control strategy lacks collaboration, and attenuation risk prevention and control lags are solved.

The invention relates to the technical field of community new energy control, and discloses an orderly and rapid charging new energy control method, which comprises the following steps: collecting photovoltaic output data, power grid voltage / current data, user charging behavior data and battery state parameters in real time; generating a dynamic charging strategy based on the power grid load data, the time-of-use electricity price information, the photovoltaic output fluctuation range and the battery health state evaluation result; generating a corresponding local optimization strategy based on the operation state data of each charging pile; an economic index and a technical index are calculated, and when any index exceeds a preset threshold value, a strategy adjustment instruction is triggered, and a charging mode switching threshold value is updated; an equipment health index is generated by combining inverter temperature, coil coupling efficiency and insulation impedance parameters with historical fault data, and maintenance early warning is triggered when the health index is lower than a safety threshold value. According to the invention, the electricity cost of the user can be reduced on the basis of improving the multi-energy collaborative optimization capability of the charging facility in the residential area.

The invention provides a battery car dynamic charging optimization management system based on battery health state evaluation, and belongs to the technical field of battery car charging management. The system comprises a data acquisition module which is connected with an environment sensing device and a battery management system and acquires environment and battery parameters in real time; the data storage module is used for storing an initial training data set, a charging and discharging data set and a battery aging feature library; the model building module is used for building a battery health state evaluation model through a migration strategy and building a response model through a modeling strategy; the health state evaluation module is used for extracting associated features with a critical damage threshold value as a core through a mapping algorithm based on the battery parameters, the environmental parameters and an aging feature library; and the charging strategy generation module comprises a strategy generation unit, a reference parameter generation unit and a dynamic correction unit. The system effectively improves the adaptability of battery car charging, guarantees the efficient and stable operation of the battery, and remarkably improves the safety and prolongs the service life of the battery.

The invention discloses a new energy automobile dynamic charging power adjustment method considering a power grid load, and aims to solve the problems of power grid overload and non-fine regulation and control caused by concentrated charging of new energy automobiles. The method is executed by a regional charging coordination server and comprises the following steps: acquiring a real-time load value and a safety threshold value of a target line of the power distribution network; collecting real-time charging aggregation data of each charging station in the jurisdiction, wherein the real-time charging aggregation data comprises the power of each charging pile and the state of charge of a vehicle battery; calculating the load margin of the power grid and determining the total charging power needing to be adjusted; the charging urgency degree coefficient of each charging pile is calculated based on the state of charge of the vehicle battery, the total adjustment amount is distributed to each charging station according to the coefficient and the total power of the charging stations, and the initial power adjustment amount is generated; according to the invention, the real-time, collaborative and refined regulation and control of the charging load from the global perspective of the power grid is realized, under the premise of ensuring the safe operation of the power grid, the highly urgent charging demand is preferably met, and the resource allocation and user experience are optimized.

The invention provides a dynamic impedance matching charger based on battery aging, a method, electronic equipment and a medium. The charger comprises a master control unit, and a battery state monitoring module, an aging grade evaluation module, a dynamic charging control module, a battery cell balancing module, an optimization control module and an anti-interference module which are connected with the master control unit to cooperatively realize charging closed-loop control. The battery state monitoring module injects a preset frequency alternating current signal and outputs an impedance parameter, a charge state and a temperature parameter; the aging grade evaluation module outputs a battery aging grade in combination with a preset model; the dynamic charging control module is matched with an adaptive charging mode instruction; the battery cell balancing module calculates the battery cell impedance difference, and balancing operation is executed if the battery cell impedance difference reaches the standard; the optimization control module generates an optimized current instruction through a preset algorithm according to the related parameters, and superposes the optimized current instruction to the reference current; the anti-interference module improves the signal-to-noise ratio of collected signals to a preset standard through isolation and shielding design.

The invention relates to the technical field of intelligent parking management, and discloses a curb parking dynamic charging and fee evasion prevention and control method based on multi-dimensional data fusion, which comprises the following steps: a data fusion reconstruction step: receiving a video stream, sensing a parking space state and reporting data through mobile inspection, performing fusion processing through space-time alignment and a confidence decision algorithm, and obtaining a data fusion result; outputting a standard parking event sequence; a dynamic charging decision-making step of matching a charging strategy model including time-phased elastic rate parameters according to the time-space attribute of the event sequence, calculating the cost and verifying the parking rights and interests in real time, and generating a parking order; and a fee evasion risk real-time prevention and control step: constructing a vehicle behavior portrait feature vector based on the event sequence and the historical order, obtaining a real-time risk level through a pre-trained risk grading model, and triggering a cascade response disposal action according to the real-time risk level, including exit interception and recovery of a high-risk vehicle. According to the invention, the charging accuracy is improved, and the rate dynamic adjustment and the active and accurate prevention and control of the fee evasion behavior are realized.

The invention discloses a 5G base station micro-photovoltaic multi-source data dynamic charging method and system, and belongs to the technical field of 5G base station charging. Multi-source data (including a base station operation state, weather forecast and a regional power consumption task) are integrated, an LSTM and XGBoost fused fault prediction model, time convolutional network power consumption demand prediction and a multi-target optimization model (optimizing power grid power purchase cost, energy storage loss and photovoltaic utilization rate) are adopted, a charging strategy is dynamically generated in combination with a cloud, and the power consumption of the power grid is optimized. And the strategy is adjusted in real time based on the fault prediction result. According to the method, the optimized strategy is executed by remotely controlling the micro-photovoltaic equipment, global energy scheduling driven by multi-dimensional data is realized, the photovoltaic utilization rate is remarkably improved, meanwhile, through a fault feedforward mechanism and dynamic weight adjustment, the operation cost is reduced on the basis of guaranteeing the power supply stability, and the power supply efficiency is improved. The problems of data island, response lag, fault vulnerability and the like in a traditional scheme are solved.

The invention discloses a high-reliability storage unit fault-tolerant control system, which relates to the technical field of storage unit fault-tolerant control and comprises a dynamic charge mapping model module, a potential inversion driving link module, a multi-channel phase conjugate regulation and control module, a nonlinear charge turn-back channel module and a self-adaptive capacitance balance control module. And the dynamic charge mapping model module is used for constructing a dynamic charge mapping model, extracting a potential transition curve in a high-frequency read-write switching stage by taking a parasitic capacitance real-time response parameter of a parallel bit line in the storage unit as an input variable, and generating a dynamic coupling map for identifying a pseudo-synchronous charge accumulation region based on the potential transition curve. According to the invention, real-time suppression and energy balance of parasitic capacitance are realized through dynamic charge mapping and potential inversion, and potential stability of a bit line is maintained; and energy closed-loop control is realized through nonlinear charge turn-back and self-adaptive capacitance regulation and control, charge regeneration is prevented, so that the stability and the reliability of the storage unit are improved, and the service life of the storage unit is prolonged.

An electric vehicle charging control device includes an electronic dynamic charging schedule generator, a non-transitory computer readable medium and an electronic communicator. The non-transitory computer readable medium stores vehicle profile data and building profile data. The electronic communicator is configured to receive profile updates to the vehicle profile data from an electronic user interface. The electronic controller is programmed to generate a driver charging profile based on the vehicle profile data and the building profile data. The electronic controller is programmed to update the driver charging profile based on the electric vehicle user's behavior. The electronic controller is programmed to generate a charging schedule for the electric vehicle based on the updated driver charging profile. The electronic controller is programmed to controlling the charging port in accordance with the charging schedule upon the electric vehicle user confirming acceptance of the charging schedule on the electronic user interface.

An indication that a ride associated with an electric vehicle has ended is received. An availability state of the electric vehicle is determined based at least on a current battery charge level of the electric vehicle and a dynamic charge threshold. Information reflecting the availability state of the electric vehicle in a set of geographic location and availability state information of vehicles comprising a fleet of electric vehicles available to be displayed is included via a user interface based at least in part on the respective availability state of the respective electric vehicles comprising the fleet of electric vehicles.

The invention relates to the technical field of ship power system energy management, and particularly discloses an energy management optimization method and system based on a ship microgrid, and the system comprises a photovoltaic power generation unit, an energy storage unit, and a diesel generator unit. The photovoltaic power generation unit is provided with a maximum power point tracking controller to achieve the maximum utilization rate of solar energy, the energy storage unit comprises a storage battery and a bidirectional power converter, the charge state is monitored in real time, a safety threshold value is set, and the diesel generator unit serves as a standby power supply. Based on an improved logic threshold control mechanism, a photovoltaic power generation unit is used as a main energy source and works at a maximum power point; the energy storage battery is a secondary buffer unit, a charge state safety threshold value is set, dynamic charging and discharging are carried out, and when photovoltaic output is surplus and the storage battery does not reach the upper limit, surplus electric energy is stored in the storage battery.

The invention discloses an electric vehicle charging pile intelligent management system and method. The system comprises a reservation distribution module, a behavior monitoring module, a credit management module, a resource scheduling module and an excitation feedback module. The reservation distribution module dynamically distributes charging pile resources based on the user credit score and generates an encryption certificate; the behavior monitoring module is used for detecting malicious pile occupying and appointment breaking behaviors in real time through multi-source sensor fusion; the credit management module dynamically calculates a user credit score and triggers a hierarchical management and control strategy; the resource scheduling module flexibly schedules charging resources according to the abnormal event; the excitation feedback module provides dynamic charging excitation according to the performance condition of the user. The system realizes dynamic credit distribution, abnormal behavior real-time monitoring, resource flexible scheduling and intelligent incentive feedback through multi-module cooperation, effectively improves the resource distribution efficiency, enhances the supervision timeliness, and optimizes the user incentive effect.

The invention relates to the field of charging power distribution, in particular to a real-time power intelligent distribution method and system for a liquid cooling charging pile. The method comprises the following steps: obtaining a real-time monitoring log of a liquid cooling pipeline, carrying out instantaneous cooling power fluctuation evaluation, and generating cooling behavior characteristic data; real-time current and voltage waveform data are collected, interface charging power demands are charged one by one, and accurate charging power demands are generated; carrying out cooling request analysis on the liquid cooling pipeline according to the cooling behavior characteristic data to obtain a cooling request priority; performing dynamic safe charging power upper limit calculation based on the precise charging power demand and the cooling request priority, thereby dynamically and safely constraining the power; and carrying out dynamic charging power distribution decision according to the dynamic security constraint power, and carrying out post intelligent power optimization. According to the invention, optimization of power distribution logic is realized, and efficient and safe charging power distribution of the charging gun is improved.

The invention discloses an electric vehicle charging scheduling optimization method based on the Stackelberg game, and the method comprises the steps: constructing a system model of a light storage charging station, and defining an energy management strategy; modeling the interaction relationship between the optical storage charging station and the plurality of electric vehicles as a Stackelberg Markov game; constructing an agent network for the leader agent and each follower agent; in each time step, the leader agent formulates a charging price and an energy storage scheduling strategy in advance and broadcasts the charging price and the energy storage scheduling strategy, and each follower agent decides respective charging power in parallel according to the charging price and the energy storage scheduling strategy; after all the intelligent agents execute actions, empirical data are stored in a local empirical playback pool; each agent samples empirical data to update the agent network; and obtaining the optimal charging station dynamic charging price and energy storage scheduling strategy and the optimal charging strategy of the electric vehicle until the strategies of all the intelligent agents converge, thereby realizing the maximization of the operation income of the optical storage charging station. According to the invention, the operation income of the optical storage charging station can be maximized.

The utility model provides a high -power dynamic charging pile structure relates to charging pile technical field, and the air outlet plate spare is connected on the casing, and the water drain support fixedly connected in the side of air outlet plate spare near casing inside, sets up the air inlet louver plate spare above the water drain support, the air inlet hole is set up in the upper position of air outlet plate spare, the lower position of air outlet plate spare sets up the external water drain hole, the height position of air inlet hole corresponds air inlet louver plate spare, the height position of external water drain hole corresponds water drain support. The utility model discloses the setting of air inlet louver plate spare and water drain support, and the flow track of air in air inlet louver plate spare area will repeatedly collide to the surface of folding frame and baffle, even if there is rainwater from the air outlet plate spare and enters, and the surface of folding frame and baffle is collided after immediately falls down under the action of gravity, and the rainwater droplet is gathered in the water drain support, and is discharged from the external water drain hole and the casing in time, improves the protection effect to each electrical element.

The invention relates to the technical field of photovoltaic energy storage management, and discloses a megawatt photovoltaic and energy storage integrated efficient energy management system. The system comprises an energy acquisition module, a dynamic threshold analysis module, a coordination control module, a multi-objective optimization module and a real-time correction module. The energy acquisition module converts a photovoltaic array output power curve and energy storage battery charging and discharging state data into a discrete sequence marked by timestamps through a multi-source sampling protocol; the dynamic threshold value analysis module generates an allowable fluctuation threshold value band based on the power sequence characteristics, and divides an energy storage dynamic charging and discharging power interval; the coordination control module combines the power deviation degree and generates a power distribution instruction; the multi-objective optimization module adopts a rolling time domain strategy to generate an optimization combination; and the real-time correction module monitors the deviation and feeds back an adjustment threshold band. According to the system, the photovoltaic and energy storage collaboration is improved, the stable operation of the megawatt photovoltaic power station is ensured, and the energy utilization is optimized.

The application discloses a method for screening lithium ion battery self-discharge, comprising the following steps: obtaining N qualified battery cells after formation aging; heating and aging the obtained N battery cells; placing the battery cells after heating treatment for a first standing time, and then performing constant current discharge for a first preset time, wherein the constant current discharge capacity is recorded as a first capacity; performing constant current discharge after the N battery cells are fully charged by constant current and constant voltage, wherein the constant current discharge capacity is recorded as a second capacity; calculating the average value of the capacity attenuation rate of the N battery cells during heating and aging based on the first capacity and the second capacity; beneficial effects: the first capacity ratio screening mainly eliminates battery cells with abnormal chemical self-discharge, the second static voltage drop screening mainly eliminates battery cells with large physical self-discharge, and the third voltage drop screening after dynamic charge and discharge cycles can effectively capture battery cells with weak physical self-discharge that escape in the first voltage drop screening.

The invention provides a charging and discharging optimization system based on an energy storage battery, and relates to the technical field of energy storage battery equalization management, and the system comprises a parameter collection module which collects the real-time state data of each battery; the anomaly identification module is used for carrying out multi-parameter weighted clustering processing on the real-time state data by adopting a clustering algorithm to obtain the comprehensive anomaly degree of each battery; the power evaluation module is used for respectively calculating a charging capability evaluation value and a discharging capability evaluation value of each battery; the coordinated distribution module is used for respectively carrying out differential control on a charging mode and a discharging mode based on the charging capability evaluation value, the discharging capability evaluation value and the comprehensive abnormality, and adopting a progressive current distribution strategy based on the comprehensive abnormality in the charging mode to obtain charging current distribution; and in the discharge mode, a layered protection strategy based on capability evaluation is adopted to obtain discharge current distribution. According to the invention, accurate identification of abnormal batteries, accurate evaluation of dynamic charging and discharging capability of each battery and intelligent execution of a differentiated coordination distribution strategy can be realized.

The invention relates to the technical field of charging management, and discloses a wheel self-energized anti-overturning dynamic charging management device, which comprises a power generator rotating along with a wheel and converting mechanical energy into electric energy; the three-phase rectifier module is used for converting three-phase alternating current output by the generator into direct current; the voltage detection and overvoltage protection module is used for protecting and controlling the charging process; the DPM charging management module is used for dynamically adjusting the charging power; the servo module is used for carrying out auxiliary control on the working state of the generator; and the weighting block deflects in the power generation process, and the deflection state of the weighting block changes along with the change of the output power of the generator. A weighting block is used as a fixed end of a generator, so that the deflection attitude of the weighting block is associated with the output power of the generator, a DPM charging management module and a servo module are introduced for cooperative control, dynamic adjustment of the output power of the generator is realized, and an attitude-power linkage management mechanism under a wheel self-energized condition is constructed from the structure and control level.

The invention provides an echelon utilization battery module health state assessment method based on dynamic image features. The method comprises the following steps: establishing a data set containing multi-dimensional characteristic parameters of a battery monomer; establishing a multi-parameter coupling characteristic model; acquiring charging voltage curve image information, current curve image information and capacity change information of the single battery; extracting image features representing the level dynamic response of the battery module, and constructing a model of the health state of the battery module, which does not involve the dynamic charging behavior of the module-level battery; establishing an inconsistency parameterized model in the battery module; extracting a characteristic value representing the dynamic charging behavior of the module-level battery; establishing a mapping relation model of the health state and the dynamic charging behavior of the battery module; and inputting the image features and the feature values into the mapping relation model to evaluate the health state of the battery module. According to the method, performance change caused by inconsistency is represented through the dynamic charging curve image, and accurate evaluation of the health state of the echelon utilization battery module is realized.

A fixed-point charging pile management method for an intelligent electric bicycle is suitable for the intelligent electric bicycle connected with a fixed-point charging pile, and the fixed-point charging pile management method comprises the following steps: S10, the fixed-point charging pile obtains the battery power of the intelligent electric bicycle, and obtains a charging mode selected by an application program through a cloud; s20, the fixed-point charging pile determines the time period electricity price, and a dynamic charging curve is formed based on an optimization algorithm in combination with the charging mode and the battery electric quantity; s30, according to the dynamic charging curve, the fixed-point charging pile controls output power to charge the intelligent electric bicycle; and S40, continuously detecting the battery electric quantity and the charging mode by the fixed-point charging pile during charging, and updating the dynamic charging curve in real time according to the time period electricity price so as to dynamically adjust the output power of the fixed-point charging pile to charge the intelligent electric bicycle.

The application discloses a dynamic charging coordination method, system, equipment and medium under open sea grid monitoring, relates to the technical field of open sea monitoring and energy management, and comprises grid dynamic division and equipment priority allocation; the light receiving efficiency is optimized by adjusting the inclination angle of the photovoltaic film, a task adjustment and energy management balance mechanism is constructed, and abnormal detection and cooperative response are carried out based on a multi-sensor fusion technology. The method disclosed by the application carries out grid dynamic division and equipment priority allocation, optimizes the grid boundary by using a hierarchical quadtree algorithm and real-time data, improves the utilization rate and monitoring accuracy of monitoring resources, optimizes the inclination angle of the photovoltaic film and the task energy management balance mechanism, improves the task completion efficiency while ensuring long-time endurance of the equipment, and accurately identifies complex abnormal events and quickly allocates response tasks based on the abnormal detection and cooperative response of the multi-modal sensor fusion technology, thereby improving the efficiency and intelligent level of the monitoring system as a whole.

The invention discloses a dynamic charging time planning method, system and device considering a first arrival first service constraint, and a storage medium, belongs to the crossing field of an intelligent traffic system and an energy internet, and solves the problem of space-time dynamic distribution of charging resources in a large-scale road network. The method comprises the following steps: setting a regional road network range and extracting a topological structure thereof; a state planning space including time, position and electric quantity is constructed, and vehicles in a road network are divided into three types: vehicles without charging requirements, non-reservation user new energy vehicles and reservation user new energy vehicles; the proportion of the reserved charging piles set in the service area is matched with the proportion of the reserved charging vehicles in the total number of the new energy vehicles; a coupled HJB-FPK equation system is established; the reservation density is listed into an FPK equation, and it is determined that the constraint condition of the FCFS service is established in each period; a rolling optimization mechanism is adopted to realize the minimum total cost of the vehicle arriving at the destination under the FCFS constraint, and the charging problem of the new energy vehicle in the road network travel peak period is effectively solved.

The application provides an EMS management method and device suitable for multiple types of batteries and a storage medium, relates to the field of battery management, and solves the technical problems that the prior art is difficult to dynamically balance charging according to user characteristics and battery characteristics when multiple types of batteries are simultaneously charged in a small range, and is difficult to design a self-sacrifice mechanism of the battery without affecting user demand; the method comprises the following steps: obtaining a battery for cooperative charging based on a charging port number, and determining whether to perform cooperative charging; if yes, determining the latest full charging time of each battery for cooperative charging according to historical use data of each battery for cooperative charging, and determining the charging power of the battery based on the latest full charging time and the battery power; if no, obtaining the dynamic charging power of the battery, and charging the battery according to the dynamic charging power; and the application can improve the overall charging efficiency of multiple types of batteries.

The application relates to the field of new energy power generation and advanced energy storage technology, and discloses a liquefied carbon dioxide energy storage and photovoltaic power station light storage collaborative optimization system, which comprises a power station site, a photovoltaic power generation unit is arranged on the power station site, a liquefied carbon dioxide energy storage unit is arranged on the power station site, a collaborative control center is arranged on the power station site, and a data acquisition and preprocessing unit is arranged on the power station site. The light storage collaborative optimization system can suppress photovoltaic output fluctuation, improve grid stability, and realize photovoltaic output prediction and energy storage dynamic charging and discharging cooperation. The photovoltaic output fluctuation range can be controlled within a certain range of new energy power generation and advanced energy storage, which is much lower than the fluctuation level of the prior art new energy power generation and advanced energy storage. The light storage collaborative optimization system can effectively avoid the problems of frequency fluctuation and voltage deviation caused by sudden rise and fall of photovoltaic output on the power grid, meet the grid connection requirements of the power grid for new energy power generation, and reduce the new energy power generation and advanced energy storage "abandoned light" new energy power generation and advanced energy storage rate.

The invention relates to the technical field of electric energy storage systems, and discloses a building photovoltaic micro-grid integrated management and control method based on dynamic charging and discharging optimization, which comprises the following steps: acquiring external disturbance prediction data of a building photovoltaic micro-grid system in a preset time domain in the future, and collecting actual operation state data of the system at the current moment; performing rolling optimization calculation based on a pre-established unified state space model, wherein the unified state space model can integrally describe a coupling dynamic relationship between the electrochemical state of the energy storage battery and the thermodynamic state of the building; the rolling optimization calculation is combined with the external disturbance prediction data obtained in the step S1 and the actual operation state data. By constructing a unified state space model for integrally describing the electrochemical state of an energy storage battery and the thermodynamic state of a building, deep coupling of electric energy dispatching and heat energy management is realized.

This invention relates to the field of robotic arm technology, specifically to an intelligent robotic arm for power line inspection, comprising: an end effector assembly including two hinged, opening and closing grippers that, when closed, are fitted onto a high-voltage power line and slide along it; an opening and closing drive assembly for driving the two grippers to perform opening and closing actions along the hinged rotation axis; split current transformers, each installed in one of the grippers, forming a closed magnetic core ring when the grippers are closed, thereby inducing electrical energy from the high-voltage power line; a circuit system module integrated on one of the grippers and electrically connected to the split current transformer for processing the electrical energy obtained by the split current transformer; and an extension arm connecting the robot and the grippers for delivering the end effector assembly to the installation position on the high-voltage power line. This intelligent robotic arm for power line inspection enables dynamic charging of the inspection robot, eliminating limitations imposed by the charging method and improving the robot's working efficiency.