1456 results about "Energy source" patented technology

A data-driven dynamic energy management system for the adaptive coordination of renewable and conventional energy sources, consisting of: a processing unit configured to perform real-time calculations to optimize the generation, storage, and distribution of electrical energy by continuously analyzing operational data, forecasting future energy demand, and generating control instructions to match available generation resources with forecasted consumption demand; a storage unit connected to the processing unit, configured to store records of historical energy production and consumption, environmental data, operating thresholds and learned model parameters, and to provide said data as input for the forecasting and optimization routines performed by the processing unit; a multitude of IoT-based monitoring units, each comprising at least one sensor configured to measure instantaneous parameters of generation, storage level, consumption rate and environmental conditions, with each monitoring unit being configured to periodically transmit measurement packets to the processing unit via a secure communication network; a forecasting unit implemented in the processing unit, configured to process historical and real-time data to create forecast curves for demand and generation using statistical and probabilistic forecasting techniques, and to dynamically update the weights of the forecasting model in response to observed deviations between forecasted and actual output; an optimization control unit implemented in the processing unit and configured to evaluate the outputs of the forecasting unit together with current operational data to determine a set of optimized control variables representing the target generation contribution of each energy source, and to pass these targets to a lower-level controller for execution; a controller that is communicatively connected to the processing unit and the multiple energy generation sources and is configured to regulate the operation of each source by adjusting the activation state, output level and operating priority based on the control signals received from the processing unit; an energy storage management unit comprising at least one battery array and a power conditioning circuit, configured to receive control instructions from the processing unit, store excess generated energy, release stored energy when forecasted demand exceeds available generation, and report charging and discharging characteristics in real time to the processing unit for continuous recalibration; an alarm and notification control unit connected to the processing unit, configured to continuously compare storage levels and generation reserves with stored operating thresholds, trigger predefined responses when critical or abnormal conditions are detected, and transmit acoustic, visual, and digital remote alerts to designated operators; a user interface terminal connected to the processing unit, configured to display real-time generation statistics, demand forecasts, energy storage status, and system alerts, and to accept operator-defined parameter inputs that are transmitted to the processing unit for recalibration of forecast or optimization parameters; and a secure server interface configured to synchronize operational logs, learning data, and performance indicators with a remote monitoring or analysis server for centralized monitoring, long-term data analysis, and distributed decision support.

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 multifunctional cycle power generation system and method by a gravity lever. The system comprises a supporting rack and a balance weight arranged on the supporting rack and slidably matched with the supporting rack, wherein engines are arranged on one side or two sides of the balance weight; the input shaft of each engine is connected to a transmission shaft; two or more single-directional clutches are fixedly connected to the middle of the transmission shaft; the locking directions of the single-directional clutches are same, gears are fixed to the peripheries of thesingle-directional clutches, and a rack matched with each gear to drive the transmission shaft to rotate is arranged next to each single-directional clutch; at least one pair of racks is arranged on the upper part and the lower part, separately, the racks and the balance weight which reciprocates are in driving movement and the balance weight is arranged on the supporting rack to swing through a lifting mechanism in a reciprocating manner. As the balance weight which swings in the reciprocating manner pulls the racks to drive the transmission shaft to rotate in the single direction, multiple engines can be driven synchronously to generate electricity synchronously, and the power needed by a supporting rack lifting device is alleviated greatly by means of a swing mode like to a lever, so that the energy sources are saved and the power generation efficiency is improved greatly.

The invention discloses a water-wind-light combined intelligent control system based on multi-energy coordinated control, and belongs to the technical field of multi-energy coordinated control, and the system comprises the steps: firstly collecting environment and operation parameters of wind power, photovoltaic and hydroelectric equipment, and carrying out the preprocessing of the environment and operation parameters to form a structured data set with a space-time label and a dynamic sampling identifier; performing space-time correlation analysis on the data set, constructing a wind power fluctuation and hydropower regulation margin real-time response matrix and a photovoltaic output attenuation and hydropower storage capacity compensation time sequence correlation model, and quantifying the multi-energy dynamic complementation degree and grading the data credibility through a two-dimensional coupling algorithm; then combining with a historical meteorological scene association rule base, constructing a water-wind-light combined power supply capability prediction model containing an energy characteristic mutual compensation coefficient, and generating a hierarchical regulation and control strategy with a space-time priority; and finally, executing a regulation and control strategy to complete parameter adjustment, continuously monitoring through closed-loop feedback, and triggering multi-energy collaborative complementary regulation when the single energy regulation capability is saturated, thereby realizing water-wind-light efficient collaborative control.

Apparatuses and methods for drying an object are provided. An apparatus for drying an object may include a first airflow channel that has an airflow inlet and an airflow outlet. The apparatus may also include one or more radiation energy sources configured to provide thermal radiation toward the object. The apparatus may also include an airflow generating element configured to provide an airflow by effecting the airflow into the first airflow channel through the airflow inlet and direct a first portion of the airflow in the first airflow channel toward the airflow outlet. The apparatus may further include an airflow guide assembly configured to provide a second airflow channel through which a second portion of the airflow in the first airflow channel is guided to a target region. The target region abuts at least one of the one or more radiation energy sources.

An electrical line selection system comprising a circuit module configured to connect energy sources with multiple line outputs. The circuit module has a number of inputs configured to connect to energy sources, including rechargeable battery systems, and a number of outputs configured to connect with other electrical systems such as other battery systems, loads, charging sources, and various AC or DC power supplies. A switching circuit is contained by the circuit module and a controller manages the switching circuit based on desired connections and strategies for managing power supplies and current sinks.

The invention discloses a fuel cell hybrid electric vehicle power distribution method based on heuristic action planning deep reinforcement learning. The method comprises the following steps: establishing a power distribution system model of a fuel cell hybrid electric vehicle equipped with a lithium battery and a super capacitor; a power layered structure is provided, a deep reinforcement learning model of the fuel cell hybrid electric vehicle is designed, a probability transfer matrix of required power is constructed, and model training is performed in a data driving mode; designing a reward function by adopting an equivalent consumption minimum strategy, and guiding optimization of an energy management strategy by fuel economy; the motion space of deep reinforcement learning is improved by adopting heuristic planning, and smooth output of the fuel cell is kept on the premise of reducing equivalent hydrogen consumption. According to the method, power distribution of the three-energy-source fuel cell hybrid electric vehicle can be achieved in a complex and random driving environment, hydrogen consumption is reduced, dynamic adaptability to different driving conditions is improved, and meanwhile the method has the potential of real-time application.

The invention relates to the technical field of nuclear reactor safety, and particularly discloses a reactor waste heat export, recovery and comprehensive utilization system and method based on a heat pipe, and the system comprises a nuclear energy generation system, a secondary loop energy conversion system, a primary loop waste heat discharge system, a secondary loop waste heat discharge system, and a waste heat recovery and comprehensive utilization system. According to the waste heat recycling system, the heat pipe can be used for heat transfer and storage under the peak regulation operation condition, the nuclear heat use efficiency is remarkably improved, the requirements of various types of energy sources such as electricity and heat are met, and passive export of reactor core waste heat can be achieved through multi-natural-circulation coupling cooperative operation under the condition of a whole-field outage accident. By means of the efficient heat transfer characteristic and the modularization characteristic of the heat pipes, independent operation of the heat pipes can be achieved, the problem of single-point failure of the system can be avoided, meanwhile, separation of a reactor coolant and a cooling medium of a waste heat removal system can be achieved, the inherent safety of a nuclear reactor is remarkably improved, and the requirements of multi-purpose scenes are met; and the purpose of fully utilizing resources is achieved.

The invention discloses a diesel-storage intelligent micro-grid system. A diesel generator charges an energy storage unit or cooperatively supplies power when power supply is insufficient; the battery energy storage unit stores electric energy and supplies power to a load; the micro-grid energy management system dynamically coordinates the output proportion, and a harmonic suppression module suppresses harmonic interference; the load prediction module predicts load power change; the transient response control module deals with transient power impact; the power distribution system is connected to a main power supply and is switched to a diesel generator power supply mode when power supply of the main power supply does not meet requirements; when the diesel generator supplies power, the bidirectional converter converts electric energy into charging current of the energy storage unit and inhibits harmonic interference; when the energy storage unit supplies power, the direct current is converted into the alternating current required by the load. According to the invention, seamless switching of multiple energy sources, active stabilization of power fluctuation, flexible conversion of electric energy forms, optimization of energy distribution efficiency and comprehensive improvement of the survivability of the micro-grid can be realized.

The invention relates to an integrated energy system optimization method considering a carbon emission reward and punishment mechanism and shared electrochemical energy storage, and the method comprises the following steps: carrying out the modeling of an integrated energy system which comprises energy supply, energy conversion, load and shared electrochemical energy storage; constructing a peak-flat-valley period stepped carbon emission mechanism considering the carbon emission difference of different energies and a dynamic carbon price factor, and determining a corresponding carbon transaction cost / reward according to the total carbon emission of the integrated energy system in a scheduling period; based on a capacity leasing and power service mechanism, modeling is carried out on the cost of the shared electrochemical energy storage mode; an optimization scheduling problem is constructed by taking system operation cost minimization and clean energy utilization rate improvement as targets; and solving the optimization scheduling problem to obtain an optimal output scheme and an energy storage charging and discharging strategy of each energy device in the integrated energy system, thereby realizing optimization of the integrated energy system.

The invention belongs to the technical field of metal processing, and discloses an automatic welding method and system.The method comprises the steps that a functional gradient transition layer is arranged between a steel workpiece and a copper workpiece, components of the transition layer change in a gradient mode from a Ni-rich layer to a Ni-Cu solid solution layer in the thickness direction, and the transition layer is doped with nano reinforced particles or rare earth elements; the metallurgical compatibility is fundamentally improved; in the welding process, a composite energy source and an auxiliary physical field are adopted, and a sensor system is used for monitoring multi-modal data in real time; monitoring data are input into a predictive control model based on artificial intelligence, the model can predict the defect trend of a future moment, and welding parameters are actively adjusted in a feedforward mode. According to the method, the problems that in a traditional method, intermetallic compounds are difficult to inhibit, and process control lags are solved, and a welding joint which is free of cracks and pores, extremely thin in IMC layer and excellent in mechanical property can be obtained.

The invention belongs to the technical field of multi-energy micro-grid system optimization scheduling, and particularly relates to a multi-energy micro-grid distribution robust low-carbon economic scheduling method based on deep learning, electronic equipment and a medium. According to the method, a mathematical model of a multi-energy micro-grid system is established according to coupling characteristics of various energy sources among power systems. In order to improve the economical efficiency and the low-carbon property of the system, a load demand response mechanism and a carbon transaction mechanism are adopted, and an electric heating load demand response model and a reward and punishment type stepped carbon transaction model are constructed. In order to solve the wind and light uncertainty of the integrated energy system and improve the robustness of the system, a scene set of uncertain variables is generated by using a conditional generative adversarial network in deep learning, and the generated scenes are clustered by using a K-means clustering method to obtain typical scenes. In order to obtain more real probability distribution, a fluctuation range of a typical scene is constrained by using a comprehensive norm, and a probability distribution fuzzy set of uncertain variables is obtained. And based on the constructed fuzzy set, the demand response model and the reward and punishment type stepped carbon transaction model, a two-stage distribution robust low-carbon economic optimization model of the multi-energy microgrid is established, in the first stage, an energy storage equipment start-stop plan of the system is determined, and in the second stage, an initial plan is adjusted and supplemented after uncertainties are revealed. And finally, carrying out iterative solution on the established model by utilizing a column and constraint generation method to obtain an optimal scheduling scheme, thereby ensuring the low-carbon property, the economical efficiency and the robustness of the system.

The invention discloses a PEMFC (proton exchange membrane fuel cell)-ORC (organic Rankine cycle)-TEG (thermoelectric generator) coupling-based waste heat utilization system and a coupling method. A PEMFC module, an ORC module and a TEG module are coupled; the system comprises a fuel cell, a TEG assembly, a condenser, a delivery pump, a pressure pump, a cooling water storage tank, an evaporator, an expansion machine, a filter, a humidifier, an ejector, a compressor and an electromagnetic valve. Heat carried by cooling water in the PEMFC cooling system is used as a main energy source for waste heat recovery. As the heat taken away by the cooling water is far greater than the directly discharged waste heat, the cooling water has higher enthalpy value and excellent heat recovery potential. By constructing a reasonable heat recovery path and a heat exchange network, the waste heat gradient utilization efficiency can be remarkably improved, and the higher primary energy utilization rate is achieved. And efficient recovery and gradient utilization of the waste heat of the PEMFC are realized.

A multiport converter designed to supply direct current loads comprising one or more energy sources, a battery, a multiport DC-DC converter connected to the energy sources and to a load, an IoT device for communication and control of the system. The multiport DC-DC converter further comprises an energy management system for selectively controlling the charging or discharging of the battery and the amount of energy directed to the load based on predictions of energy generation from the energy sources, based on a load demand and based on optimized scenarios. The multiport converter is used in green hydrogen generation plants powered by renewable energy sources, such as wind and photovoltaic energy; and a system capable of self-managing and ensuring better use of energy from the sources and better efficiency of green hydrogen generation.

A method for controlling a marine drive configured to propel a marine vessel. The method includes receiving a destination for the marine vessel, receiving a demand request for operating the marine drive, and operating the marine drive at an actual demand corresponding to the demand request. The method further includes determining a required energy for the marine drive to propel the marine vessel to the destination at the actual demand and determining a remaining energy of an energy source available for operating the marine drive. The method further includes comparing the required energy to the remaining energy and, when the remaining energy is less than the required energy, automatically iteratively reducing the actual demand for operating the marine drive until the remaining energy equals or exceeds the required energy determined for the marine vessel to reach the destination.

The invention discloses an energy control method and device for a flying vehicle, electronic equipment and a readable storage medium. A solar cell layer, a heat insulation layer and a thermoelectric power generation layer are sequentially integrated on the surface of the flying vehicle from top to bottom, and the method comprises the steps of obtaining first electric energy converted by the solar cell layer in response to the fact that the flying vehicle is located in a light environment, and obtaining second electric energy converted by the heat insulation layer in response to the fact that the temperature difference between the flying vehicle and the external environment is larger than a first preset temperature difference threshold value; acquiring second electric energy converted by the thermoelectric power generation layer; performing voltage conversion on the first electric energy to obtain first target electric energy, and performing voltage conversion on the second electric energy to obtain second target electric energy; charging a battery of the flying vehicle based on the first target electric energy and the second target electric energy; the electrical energy stored in the battery is distributed to the electrical load based on an energy consumption demand of the electrical load of the flying vehicle. The technical problem that the energy source of the flying vehicle is single is solved.

The invention discloses a space radiant energy collection and conversion system, which relates to the technical field of energy conversion, and comprises a motor, a main shaft, a steam turbine, an expansion machine and a synchronous generator, a clutch I and a clutch II are respectively mounted on the main shaft on the right side of the motor and the left side of the steam turbine; and a transmission I, a transmission II and a transmission III are sequentially mounted on the main shaft between the clutch I and the clutch II. According to the space radiant energy collection and conversion system, energy sources are infinite, and radiant energy in air and water is utilized and is an inexhaustible energy source; the cost is extremely low: the cost of generating one kilowatt-hour can be reduced to one minute; the system does not depend on fossil fuel, and pollution of exhaust emission to the nature is avoided.

A system includes a converter that distributes electric energy from an energy source to a load. The converter includes a dual active bridge. The system includes interfaces coupled to the converter. The system also includes a controller system that includes the interfaces and a controller. The controller system includes processors that perform determining of modulation control attributes based on characteristics of the converter, the modulation control attributes including one or more modulation control parameters and one or more modulation control modes corresponding to one or more phase shift techniques, obtaining operational condition information within the converter, the operational condition information corresponding to a component within the converter or an output of the converter, iteratively adjusting the modulation control attributes based on the operational condition information and controlling the converter based on the iteratively adjusted modulation control attributes.

The invention discloses a composite fiber membrane for hydrogen production and oxygen production through light-driven full water decomposition and a preparation method of the composite fiber membrane, and belongs to the technical field of photocatalysis technology and nano material preparation, and the composite fiber membrane shows excellent photothermal conversion performance in the reaction of hydrogen production and oxygen production through light-catalyzed water decomposition and also has efficient water transmission capacity. The stability and the reusability are relatively high. According to the preparation method, a Ti source compound, a Sr source compound, tetraethyl orthosilicate and a spinning solution are used as raw materials for electrostatic spinning, and after pre-oxidation and carbonization treatment at a certain temperature, the SrTiO3 / SiO2 composite carbon fiber membrane is obtained, and Cr2O3 / Rh and CoOOH cocatalysts are supported. The fiber membrane prepared by the invention has the function of photocatalytic water decomposition to produce hydrogen under the irradiation of sunlight, can stably produce hydrogen and oxygen in various water resources, is simple in process and low in cost, and can be widely applied to the fields of energy sources, environmental protection and the like.

The invention discloses an active power distribution network power flow optimization method based on a large language model, and belongs to the field of power system optimization. The method comprises the following steps: firstly, realizing optimal power flow problem modeling according to topology and equipment parameter data of an active power distribution network to be subjected to power flow optimization; designing structured cue words through an optimal power flow problem, and driving a large language model zero sample to generate a diversified heuristic algorithm initial population; and then a thinking chain evolutionary strategy is adopted, calculation errors serve as judgment criteria, another large language model is guided to simulate selection, intersection and mutation operation to achieve heuristic algorithm iterative optimization, output needed by all distributed energy sources of the active power distribution network is obtained based on the heuristic algorithm with the minimum calculation error, and power flow optimization of the active power distribution network is completed. According to the method, the core problems of low design efficiency and high dependence on expert experience of a heuristic algorithm in the complex optimal power flow problem of the active power distribution network are solved, and automatic generation of a high-quality algorithm can be realized for a user-defined problem scene.

The invention relates to an electric power energy labeling method and system, and the method comprises the steps: carrying out the preprocessing of multi-mode original data in an electric power system, obtaining the cleaned preprocessing data, and enabling the preprocessing data to comprise text data, image data, time sequence signal data and audio data; the preprocessed data is dynamically bound based on a space-time-event three-dimensional rule, a structured multi-modal data card is generated, and the multi-modal data card takes a device ID-timestamp-event type as a unique identifier and comprises a text abstract, an image thumbnail, a time sequence curve fragment and an audio waveform; based on the multi-modal data card, intelligent labeling is carried out in a man-machine cooperation mode, and an initial label set is obtained; the initial label set is dynamically optimized, label errors are corrected, a high-quality labeling result is obtained, and the high-quality labeling result is stored in a structured mode and output to a downstream application system through an API interface.

The present specification proposes a method and an apparatus for managing energy information in a next-generation wireless communication system. A next-generation wireless communication system including a 5G system may have defined therein an energy information repository function (EIRP) having a new network function capable of: exposing energy information to an AF; collecting information regarding energy of the AF; and storing and managing the energy information. The EIRF may provide energy information of a UE to the AF of a third party, and the AF may acquire energy information from the 5G system and monitor the acquired energy information. In addition, the AF may perform a system configuration based on energy efficiency, such as charging or restricting a service according to the energy information. Also, by the function, the AF may adjust service provision such as video playback by checking energy source information or carbon emission information.

The invention relates to the technical field of organic pollutant degradation, and discloses a mycobacterium and a method for degrading alkane organic pollutants. The Mycobacterium sp. Is named as SLQ-1, the Mycobacterium sp. Is preserved in the China Center for Type Culture Collection on January 15, 2024, and the preservation number is CCTCC No: M 2024107. The Mycobacterium sp. Is named as SLQ-1, and the Mycobacterium sp. Has been preserved in the China Center for Type Culture Collection on January 15, 2024. The mycobacterium can effectively degrade alkane organic pollutants, especially organic pollutants below C8, SLQ-1 can grow and breed with 3-methylpentane as a carbon source and an energy source, 3-methylpentane is efficiently degraded, and the mycobacterium can adapt to a wide temperature range and a wide pH range (the degradation rate of 3-methylpentane can reach 99% or above when the pH is 6-8 and the temperature is 30-40). In addition, the mycobacterium SLQ-1 can also take 2-methylpentane, n-hexane, n-pentane and 2-methylbutane as a carbon source and an energy source, and can efficiently degrade the 2-methylpentane, the n-hexane, the n-pentane and the 2-methylbutane.

The invention discloses a new energy station collaborative frequency modulation method, device and equipment, and belongs to the technical field of new energy power generation, and the method comprises the steps: obtaining the operation data of a multi-energy source new energy station in real time; according to the actual frequency of the power system and the active power of the station, determining a quick frequency modulation active increment required to be responded by the multi-energy source new energy station; determining the real-time weight of each energy source participating in frequency modulation according to the actual frequency of the power system, the installed capacity and real-time output of each energy source, the adjustment speed score, the adjustment precision score and the health loss coefficient; and according to the real-time weight, distributing the fast frequency modulation active increment to each energy source in proportion, generating an ideal active power regulation instruction of each energy source, and executing the ideal active power regulation instruction. According to the method, through dynamic weight and closed-loop optimization, frequency modulation tasks can be intelligently allocated, economy and equipment loss are considered, adaptive improvement of a control strategy is realized, and the frequency modulation response speed and efficiency and the power grid stability are effectively improved.

The invention relates to the field of electrical energy, and discloses an intelligent anomaly identification and recovery method for electrical energy time sequence data. Comprising the steps of collecting and preprocessing multi-dimensional time sequence data of a power terminal; local and long-term features are extracted by combining a periodic attention mechanism through a feature extraction module fusing a time convolutional network and a Transform; a residual self-supervised classifier is used for identifying multiple types of anomalies such as missing, jumping, drifting and sudden rising; the abnormal segments are repaired in a context interpolation and period fitting combined mode, and dynamic weighted reconstruction is achieved through a deformable time window; after restoration, a credibility scoring mechanism based on residual amplitude, period consistency and classification confidence is introduced, high-risk marking is carried out on low-confidence fragments, and manual rechecking or system correction is triggered; and self-adaptive updating of the model is realized through historical feedback.

A system includes a converter that distributes electric energy from an energy source to a load. The converter includes a dual active bridge. The system includes interfaces coupled to the converter. The system also includes a controller system that includes the interfaces and a controller. The controller system includes processors that perform determining of modulation control attributes based on characteristics of the converter, the modulation control attributes including one or more modulation control parameters and one or more modulation control modes corresponding to one or more phase shift techniques, obtaining operational condition information within the converter, the operational condition information corresponding to a component within the converter or an output of the converter, iteratively adjusting the modulation control attributes based on the operational condition information and controlling the converter based on the iteratively adjusted modulation control attributes.

The invention relates to the technical field of hybrid electric vehicle energy management, in particular to a hybrid electric vehicle layered reinforcement learning energy management method considering energy source life and energy consumption optimization. The method comprises the following steps: establishing an energy management system model and an energy source degradation model; energy source physical characteristics are analyzed, demanded power is processed in a layered mode, and an energy management learning strategy based on historical data is constructed; and energy management is implemented by combining the demand power change, the lithium battery, the super capacitor SOC and the degeneration degree of the energy source. Fuzzy filtering is adopted to shunt required power, a high-frequency peak value is borne by a super capacitor, and low-and-medium-frequency power is proportionally distributed by a lithium battery and a fuel battery according to the degradation degree; energy source degradation and deep reinforcement learning are fused, related parameter weighting is introduced into the ECMS, and lithium battery charging and discharging current is restrained. According to the method, comprehensive energy consumption can be reduced, energy source degradation is slowed down, the working condition application range is widened, overcharge and overdischarge of the lithium battery are avoided, the service life of the lithium battery is prolonged, and the SOC of the energy storage element is stabilized in a reasonable interval.

The present disclosure relates to an apparatus for powering an implant for a human patient and a method for powering an implant for a human patient. Wherein said apparatus comprises an implantable energy source for providing energy to the implant, an energy provider connected to the implantable energy source and connected to an energy consuming part of the implant, the energy provider being configured to store energy to provide a burst of energy to the energy consuming part, wherein the energy provider is configured to be charged by the implantable energy source and to provide the energy consuming part with electrical power during startup of the energy consuming part.

A method for charging a battery pack via an offboard energy source uses an interleaved boost converter and closed-loop control. The energy source outputs a charging current via a DC charge port during a direct current fast-charging (DCFC) process. A controller detects a voltage disparity condition in which a voltage capability of the battery pack exceeds a voltage capability of the energy source. In response to this condition, a rise of the charging current over time is recorded as a current trajectory and an open-loop equivalent time constant is extracted from the current trajectory. A time constant of the PI control block is set substantially equal to the equivalent time constant. The PIM is controlled in closed-loop using proportional-integral control. The charging current is controlled in a continuous current conduction mode during the DCFC process.

The invention discloses a new energy high-voltage direct current protection device comprehensive test platform, and relates to the technical field of new energy high-voltage direct current system core protection device test, and the platform comprises a power supply and energy storage module which is used for converting a 380V alternating current into a stable and adjustable direct current and storing the stable and adjustable direct current as an energy source required by a high-voltage large-current test, different test voltage requirements are met through series-parallel topology switching; and the power control and load simulation module is used for controlling on-off and adjustment of current in the test loop. By adopting the modular combination design of the super-capacitor energy storage unit, the adjustable pulse inductor and the load module, the comprehensive compatibility of high-voltage direct-current protection devices such as a relay and a fuse in various test scenes such as short circuit resistance, electric service life and limit on-off is realized, meanwhile, the system can work only by being powered by a conventional 380Vac laboratory, and the test efficiency is greatly improved. The method does not depend on an industrial high-voltage power grid or a special transformer, greatly reduces the equipment deployment threshold, and improves the test response efficiency.