7573 results about "Power capacity" patented technology

The invention relates to the field of new energy charging, in particular to a new energy charging management method for a smart city. The method comprises the steps that a municipal vehicle operation feature data set is acquired, on the basis, municipal vehicles are subjected to type division through a vehicle type classification strategy, and a municipal vehicle driving type set is determined; acquiring a municipal vehicle task set, and on the basis, tracking a dynamic task variable set of a task execution vehicle in a municipal vehicle driving type set in a task execution process; according to the dynamic task variable set, analyzing an association relationship between the dynamic task variable set and the real-time power consumption data through a multi-modal fusion strategy, and determining dynamic power change information; and acquiring a charging station information set, dynamically optimizing a charging decision in combination with the municipal vehicle task set and the dynamic electric quantity change information, and determining and outputting an optimal charging strategy. In the municipal vehicle charging decision-making process, the utilization rate of charging resources is improved, and the continuity of municipal task execution is ensured.

The invention provides a distributed energy access-oriented intelligent electric meter multi-device collaborative optimization method and device, equipment and a medium, and the method comprises the steps: carrying out the interpolation of a unified electric meter, an inverter and energy storage data granularity, building a joint time error model, obtaining calibration reference data, and completing the multi-device time synchronization calibration; based on the reference data, acquiring operation data of three devices, and using a joint energy consumption model to distinguish electric meter hardware faults and multi-device collaborative anomalies to complete fault diagnosis; calculating local line loss by combining an inverter-to-ammeter line and electric quantity data, verifying residual electricity metering deviation, and tracing and correcting settlement data to complete line loss-bidirectional metering linkage verification; associating the fault result with the corresponding relation between the long-term statistical fault type of the metering data and the deviation rate and the line loss to establish a model to predict deviation trend early warning; and determining a multi-device cooperative abnormal source and transformer area load interference relation, calculating an interference coefficient, feeding back a scheduling system, and marking a line reconstruction priority. By adopting the method, the distributed energy consumption efficiency and the operation reliability of the power distribution network are improved.

The invention relates to the technical field of battery electric quantity estimation, in particular to a lithium ion battery electric quantity accurate estimation method and system based on a BMS. The method comprises the following steps: collecting BMS original data, carrying out voltage current interval slicing, constructing a charging and discharging period node map, detecting node interruption joints, comparing slope differences to identify charging and discharging turning points, dividing independent charging and discharging periods according to the turning points, and determining current change time sequence data of each period. The actual charging and discharging electric quantity is calculated through the time sequence data, the charging and discharging difference is compared, the historical input and discharging electric quantity is further inquired, the fuzzy electric quantity range of the battery is deduced, and finally the real-time remaining available electric quantity is accurately calculated according to the fuzzy electric quantity range and the actual charging and discharging electric quantity difference and is uploaded to the BMS system. According to the invention, real-time monitoring and management of the electric quantity estimation result are realized, and the intelligent level of the battery management system is improved.

The invention discloses a power supply method and a power supply system for on-line monitoring equipment of a lightning arrester, and the method specifically comprises the steps: activating a multi-source energy module according to a preset priority order based on the operation state and environment parameters of the lightning arrester, and supplying power to the on-line monitoring equipment; based on the output characteristics of the multi-source energy module and the residual electric quantity of the on-line monitoring equipment, a constant voltage-constant current hybrid power supply strategy in a conventional mode or an anti-interference power supply strategy in an abnormal mode is executed on the on-line monitoring equipment; and processing the historical leakage current, environmental temperature and humidity and vibration spectrum characteristics of the lightning arrester acquired by the online monitoring equipment through the LSTM prediction model, predicting the energy supply trend of the online monitoring equipment in the preset future time, and dynamically adjusting the working parameters of the online monitoring equipment according to the energy supply trend. According to the invention, stable power supply of the lightning arrester on-line monitoring equipment in a complex environment is realized, and the power supply reliability and the equipment availability are improved.

The invention provides a battery dynamic equalization method and system based on cloud computing, relates to the field of battery management, and solves the technical problem of insufficient utilization of battery equalization resources in the prior art. The method comprises the following steps: a cloud calculates a fault probability index of each monomer based on acquired operation data and historical equilibrium data of each monomer in a battery pack, and marks the monomer of which the fault probability index is smaller than a preset fault threshold as a normal monomer; according to the battery state data and the power grid load data of the normal monomers, calculating the dynamic balance priority of each normal monomer; distributing equalization current and equalization electric quantity of each normal monomer based on the dynamic equalization priority to obtain an equalization strategy, and sending the equalization strategy to a local end; and the local end executes the equalization strategy, and when a re-triggering condition of the equalization strategy is met, an equalization calculation request instruction is sent to the cloud end, and the calculation process is repeated. The method is used in the dynamic balance control process of the battery pack under the scenes of energy storage, power and the like.

The invention relates to the field of battery car charger detection, in particular to a charger health state assessment method and system, and the method comprises a data collection step, a predicted electric quantity calculation step, a health state assessment step and a fault feature analysis step. A sliding time window algorithm is used for dynamically calculating electric quantity loss, a self-adaptive dynamic threshold system based on an operation state and an environment working condition is constructed, fault characteristics are analyzed in combination with a nonlinear fusion model and an equipment aging factor, and accurate evaluation of the health state of the charger and rapid fault positioning are achieved. And the evaluation comprehensiveness, accuracy, threshold dynamic nature and fault analysis precision are improved.

The invention relates to a battery SOC intelligent monitoring and management method based on a precise electric quantity algorithm, and belongs to the technical field of battery power generation management, and the method comprises the steps: obtaining the voltage, current, temperature and historical data of a battery in real time, and calculating an initial SOC value through an ampere-hour integral method; when the SOC is greater than or equal to 90% in a charging state, generating a first correction factor based on a voltage hysteresis characteristic and a temperature coefficient, and dynamically reducing an ampere-hour integral weight; in the discharge state and when SOC is smaller than or equal to 20%, a second correction factor is generated in combination with the polarization voltage and the temperature attenuation coefficient, and the Kalman filtering weight is increased; and fusing the correction factors through a gradient descent optimization algorithm, performing closed-loop feedback, and outputting a calibrated SOC value. According to the method, through dynamic weight distribution, a nonlinear compensation model and a closed-loop self-optimization mechanism, the problems that an extreme SOC interval is large in estimation error and a traditional method is poor in adaptability are solved, and the precision and reliability of battery management are remarkably improved.

The invention discloses a system and method for estimating the charging capacity of an energy storage lithium battery, and particularly relates to the technical field of energy storage battery management, and the method comprises the following steps: collecting dynamic parameters in the charging process of the energy storage lithium battery, and forming a dynamic data set; calculating an environmental disturbance influence index and a charging response consistency factor based on time sequence analysis and feature decoupling; constructing a two-dimensional working condition mapping matrix, identifying a current working condition area and generating a scene label; determining parameter weights of the plurality of estimation models by adopting a probabilistic reasoning mode; according to the scene state, selecting a single model output result or fusing a plurality of model output results for estimation; according to the method, the environment disturbance influence index and the charging response consistency factor are constructed, so that the complex working condition is accurately identified; scene labels are automatically generated based on two-dimensional working condition mapping and a clustering algorithm, and a plurality of estimation models are dynamically selected or fused in combination with model confidence, so that the accuracy, robustness and intelligent level of estimation are improved.

The invention discloses an orderly power utilization system for a charging pile. The orderly power utilization system comprises a cloud platform, an orderly power utilization gateway and an orderly power utilization terminal, the cloud platform is used for judging the residual power of the power transformation box through the orderly power utilization gateway; the orderly power utilization gateway is used for collecting and controlling the charging power of the charging pile through the orderly power utilization terminal; the cloud platform is provided with a basic guarantee layer and a competition layer, and the basic guarantee layer is used for distributing the lowest power to each vehicle connected with the charging pile, so that the basic charging requirement is ensured; and the competition layer calculates priority scores according to the current electric quantity, the charging remaining time and the charging power of the charged vehicles, and distributes the remaining power of the power transformation box step by step according to the priority scores of the vehicles from large to small under the condition that the total power capacity of the charging pile is not exceeded. The competition layer calculates the priority score through the current electric quantity, the charging remaining time and the charging power of each vehicle, and then distributes the remaining power of the power transformation box according to the priority score, thereby adapting to the requirements of complex scenes, and improving the charging efficiency.

The invention relates to the technical field of information, in particular to a control method and system for an intelligent photovoltaic charging pile in the technical field of automobile charging piles, and the method comprises the steps: obtaining the charging demands and residual electric quantity information of a plurality of electric automobiles, dynamically adjusting the charging power of each automobile through combining with an electric power distribution algorithm, and guaranteeing the reasonable distribution of electric power resources; acquiring real-time load data through a power grid load monitoring system, predicting a future power grid load change trend in combination with a historical load curve, and judging whether a charging strategy needs to be adjusted or not; according to historical data and real-time data, cooperative working parameters of photovoltaic power generation and storage battery power storage are optimized by adopting a machine learning algorithm, and the overall efficiency of the system is improved; a cooperative working mode of photovoltaic power generation, storage battery power storage and power grid power supply is dynamically adjusted through an intelligent optimization algorithm; if the illumination fluctuation is large, a standby power supply is started to supplement power supply, it is ensured that the charging process is not affected, meanwhile, the energy storage efficiency is optimized, and power resource waste is reduced.

The invention relates to the technical field of power system automation, in particular to a climbing-frequency modulation coordinated optimization method and system considering energy storage capacity uncertainty, and the method comprises the steps: building an opportunity constraint model of an energy storage system based on the capacity uncertainty, and enabling the opportunity constraint model to be used for describing a reliable feasible region under the deviation of energy storage electric quantity; establishing an energy storage system linearization model considering a climbing-frequency modulation power unified constraint, and realizing power coupling and sharing constraint description of two types of adjustment services; aiming at the nonlinear characteristic of the gradeability of the thermal power generating unit, establishing a piecewise linearization model of the gradeability by adopting a piecewise linearization method; and establishing a thermal power-energy storage combined climbing-frequency modulation coordinated optimization model, and solving the optimization model by adopting a quadratic programming method to obtain the climbing power and frequency modulation reserve capacity of the thermal power generating unit and energy storage. According to the method, the actual available range of the energy storage system capacity can be dynamically reflected, the electric quantity out-of-limit risk caused by the uncertainty of the energy storage capacity is avoided, and the reliability of the scheduling result is improved.

The invention relates to the technical field of fault diagnosis, in particular to a pole-mounted circuit breaker fault diagnosis method based on multi-information fusion, and the method comprises the steps: firstly obtaining electric quantity modal data such as three-phase current and coil current and mechanical quantity modal data such as mechanism vibration and voiceprint, and constructing a time-frequency domain alignment feature tensor; then, through a graph space-time attention fusion model, deeply mining physical structure association and time sequence evolution laws among heterogeneous data, and generating a dynamic space-time feature matrix; then, respectively constructing a mechanical evidence body for representing the state of the transmission chain of the operating mechanism and an electrical evidence body for representing the working condition of the vacuum arc-extinguishing chamber by adopting a feature level-decision level mixed framework; an improved D-S evidence theory is applied for fusion, when high-conflict evidences are detected, a self-adaptive arbitration mechanism is automatically triggered, conflict weights are dynamically attenuated or distributed to uncertain items, misjudgment is effectively avoided, and high-robustness collaborative diagnosis of the electromechanical state is achieved.

The invention discloses a new energy medium and long term stochastic programming method and system coupled with an electro-hydrogen water regulation power supply, and the method comprises the steps: building a power supply planning model with the minimum planning operation cost as an optimization target; bringing the new energy power supply and energy storage adjusting equipment operation model and the new energy consumption rate upper and lower limit constraint expression into a power supply planning model; in consideration of the randomness of fluctuation at two sides of a source and a load in power supply planning, based on the obtained power system operation scene set S and the power supply planning model, dividing into an investment decision-making layer and an operation simulation layer according to a time period influenced by a decision, and constructing a power supply planning two-stage stochastic optimization model based on a typical scene; and solving the power supply planning two-stage stochastic optimization model under a medium and long term planning framework, and determining the investment planning installed capacity of the adjusting power supply and the new energy in the planning level year. According to the invention, economy of medium and long term planning and power supply capacity configuration of new energy can be improved, and reasonable consumption and flexible adjustment of new energy electric power are promoted.

The invention relates to a battery internal resistance detection method and device. The method comprises the following steps: acquiring a pre-constructed association relationship based on temperature, current and internal resistance of a to-be-detected battery; in the charging process of the to-be-detected battery, when a preset condition is met, determining a first moment, and recording a charging parameter corresponding to the first moment; electric quantity integration is carried out at the first moment; in the discharging process of the to-be-detected battery, when the electric quantity integral reaches a preset threshold value, determining a second moment, and recording a discharging parameter corresponding to the second moment; and determining the internal resistance of the battery according to the charging parameter, the discharging parameter and the association relationship. According to the method, the dependence on the working condition environment, the data acquisition synchronism and the data acquisition frequency is reduced through the pre-constructed incidence relation of the temperature, the current and the internal resistance, the internal resistance of the battery is determined through the charging parameter, the discharging parameter and the incidence relation, and the detection precision of the internal resistance of the battery is further improved on the premise of not increasing extra cost.

A system includes control circuitry for identifying, during operation in a first operating mode wherein electrical power is limited by protection devices, an indicator to enter a second operating mode. The indicator corresponds to power consumption of the electrical system exceeding a power capacity of the electrical system, nearing, achieving, or exceeding a limit. In response to the indicator, the system operates in the second operating mode by retrieving reference information comprising load preferences and limits, and managing one or more loads, sources, or both to modify power consumption, power capacity, or both based on the indicator and based on the reference information. The system communicates with loads or sources, and manages branch circuit using controllable elements to prevent power consumption from exceeding power capacity. The system modifies setpoints, turns devices on or off, schedules device operation or otherwise manages the electrical system based on predetermined preferences.

The invention discloses an elevator control system with an electricity-saving quantity calculation function, which relates to the field of elevator control and comprises an energy-saving control module, a first electric energy sampling module, a second electric energy sampling module, a third electric energy sampling module, a fourth electric energy sampling module, a fifth electric energy sampling module, a battery module, a conversion module and an auxiliary power supply module, the mains supply and the battery module are used for supplying power to the auxiliary power supply module, the auxiliary power supply module supplies power to the energy-saving control module and the conversion module, the alternating-current side of the conversion module is connected with the second electric energy sampling module connected with the mains supply, and the direct-current side of the conversion module is connected with the battery module; the third electric energy sampling module is arranged between the joint of the conversion module and the battery module and the battery module, the fifth electric energy sampling module is arranged between the joint of the conversion module and the battery module and each elevator, and the fourth electric energy sampling module is arranged between each elevator and the mains supply; the first electric energy sampling module is arranged between the auxiliary power supply module and the commercial power. According to the invention, the saved total electric quantity can be calculated.

The invention relates to a multi-virtual power plant collaborative transaction method, system and device and a readable medium, and the method comprises the steps: constructing a multi-energy coupling model containing a gas turbine, an energy storage device, biomass power generation and a new energy vehicle, and generating a multi-source data set to quantify the carbon emission cost and charge and discharge constraints; a wind and light output joint probability distribution model is generated based on an F-vine Copula distribution function, and a severe scene set is screened through random sampling and scene closeness evaluation; designing a renewable energy source-load correlation coefficient and a green energy consumption compensation mechanism, and correcting a virtual power plant scheduling objective function; establishing a double-layer dynamic transaction mechanism, and iteratively optimizing an upper-layer dynamic electricity price and a lower-layer multi-source transaction electricity quantity; a multi-stage robust optimization algorithm is adopted to process the uncertainty of wind, light and electric vehicles, and a transaction strategy among multiple virtual power plants in a severe scene is generated, so that the problems of low-carbon excitation deficiency, insufficient multi-source uncertainty coping and the like are solved, and unification of economy, low-carbon property and robustness of collaborative scheduling transaction of the multiple virtual power plants is realized.

The invention relates to the field of new energy charging, in particular to a main circuit topology based on an integrated over-charging device for light storage and charging and a control method. The system is composed of the following parts: an ACDC module, a charging DCDC module, a photovoltaic DCDC module, a DCAC module and a battery, wherein the battery is used for storing redundant electric quantity and discharging the electric quantity to a charging pile for use; the invention provides a main circuit topology based on direct-current coupling, a very simple network architecture and an AI intelligent algorithm are fused to greatly expand the application scene of optical storage and charging in the overcharging field, meanwhile, a dynamic intelligent algorithm is combined, the dependence of an overcharging station on a power grid is reduced, and through an economic operation strategy, the system is more reliable and reliable. Efficient collaboration and accurate distribution of energy of all links of light, storage, charging and utilization are achieved, and the operation capacity and economical efficiency of a charging station are improved.

The invention provides a virtual power plant group resource scene adaptive scheduling method and system, and a storage medium, and the method comprises the steps: building a typical external feature model of a virtual power plant based on the resource characteristics and core parameters of different types of distributed resources; generating a feasible region of the single equipment based on power constraint, electric quantity constraint and climbing constraint of the single equipment in the virtual power plant, and aggregating the feasible region of the single equipment to form an aggregated feasible region of the virtual power plant; based on a typical external feature model of the virtual power plant and different service scene requirements, dynamically adjusting response capability index weights in different service scenes, and based on an aggregation feasible region of the virtual power plant, constructing a virtual power plant dynamic aggregation model adapted to multiple scenes; and solving the dynamic aggregation model of the virtual power plant by taking minimization of the power generation cost of the virtual power plant as a target to obtain an optimal scheduling scheme of the virtual power plant.

The invention relates to a sodium electric energy storage system dynamic partition power control method based on string type cluster level management, which comprises the following steps of: firstly, realizing physical isolation of battery clusters through a string type framework, configuring an independent power conversion module and a cluster level controller for each cluster, acquiring voltage, current, SOC (state of charge) and SOH (state of health) of each cluster in real time, and on the basis of the data, in a discharging or discharging process, determining the state of charge of each cluster; a dynamic partition strategy and automatic adjustment of power distribution are realized according to inter-cluster SOC, SOH, voltage range, temperature range, power limit and other differences, and an energy storage system is dynamically divided into a high-energy high-health area, a high-energy medium-health area, a medium-energy high-health area, a medium-energy medium-health area, a low-energy or sub-health area and a fault early warning area in a discharging and charging mode; and rapid balance of electric quantity among clusters is realized through the converter module, so that power distribution is ensured to meet power grid requirements, overcharge and overdischarge of batteries are avoided, and the service life of a battery system is prolonged.

The invention provides a vehicle control method and device, a vehicle and a storage medium, the method is applied to the technical field of hybrid power control, and the method comprises the steps that based on the current electric quantity of a power battery of the vehicle and the whole vehicle demand power of the vehicle, an initial driving mode of the vehicle is firstly determined; calculating the total power consumption corresponding to each of multiple candidate power distribution proportions in the initial driving mode, determining a target power distribution proportion in the multiple candidate power distribution proportions according to the total power consumption corresponding to each of the multiple candidate power distribution proportions, and finally determining the target power distribution proportion in the multiple candidate power distribution proportions based on the target power distribution proportion. And correcting the initial driving mode to obtain a target driving mode, and controlling the vehicle to run in the target driving mode. According to the method, the energy utilization efficiency of the whole vehicle can be maximized, it is ensured that the engine and the motor operate in respective efficient intervals as much as possible, and more stable power output can be provided for the vehicle under different road conditions.

The invention discloses a double-closed-loop cooperative control method of a direct-drive electric chassis and a power system, relates to the technical field of power control of electric special vehicles, and provides a rotating speed and torque double-closed-loop cooperative control architecture, and realizes double-core real-time cooperative operation and dynamic optimization of motor output characteristics through a 32-bit processor. A direct-drive transmission structure is combined, a traditional speed reduction device is omitted, a flat wire motor directly drives a rear axle through a transmission shaft, and a four-in-one controller is matched, so that the system loss is reduced by 33%, and the power density is improved by 15%; on the basis of real-time temperature / electric quantity data of a lithium iron phosphate battery management system, control parameters are adaptively adjusted, and the bottleneck of performance attenuation in a low-temperature environment of-35 DEG C is broken through; and a high-voltage interlocking and insulation monitoring module is integrated, and an emergency hydraulic system is automatically switched when an electrical fault occurs, so that multi-stage safety guarantee is formed. According to the technology, the energy recovery efficiency is remarkably improved by 20%, and the wind resistance stability and the extreme environment reliability are effectively enhanced.

The invention relates to the field of locomotive power battery electric quantity control, and particularly discloses a locomotive power battery electric quantity hysteresis equalization control method, which comprises the following steps that: a traction force exerting mode is reset into an axle load transfer mode, and the initial value of an electric quantity equalization compensation coefficient K is a rack axle load transfer coefficient corresponding to zero speed; judging whether the current mode is a power battery power supply mode; if yes, the TCU receives the electric quantity of a front power battery and the electric quantity of a rear power battery in real time according to the current locomotive working mode, calculates the electric quantity average value difference value, monitors the auxiliary load power and the traction motor power and calculates the power difference value; entering a hysteresis control logic process; calculating a dynamic traction force compensation coefficient, ensuring that the traction force compensation amount is matched with the actual load characteristic of the system, correcting the traction characteristic curve in real time, and dynamically compensating the electric quantity difference of the battery; and performing traction distribution control according to the locomotive speed and outputting corresponding traction.

Disclosed in the present invention are a load-prediction-based control method and apparatus for an energy storage apparatus, and a terminal device and a storage medium. The method comprises: using a preset load prediction model to perform prediction on the basis of real-time operation data, so as to obtain a predicted load value of a micro-grid within a future time period; then, on the basis of a power generation capacity and the predicted load value, determining whether there is surplus electricity after the current power generation capacity of the micro-grid satisfies a future load demand; if so, controlling an energy storage apparatus to be charged, so as to avoid the waste of electric energy; and if not, controlling the energy storage apparatus to supply power to the micro-grid, so as to ensure that the micro-grid can satisfy the future load demand, thereby effectively ensuring the stable power supply of the micro-grid.

The invention discloses a fault diagnosis method and system for a metering error of a voltage transformer, and relates to the technical field of power equipment fault diagnosis, and the method comprises the steps: obtaining the historical electric quantity data of a secondary side under the normal operation of the voltage transformer, and carrying out the noise reduction and normalization preprocessing; establishing an initial principal component analysis model according to the preprocessed historical electric quantity data, and calculating to obtain a statistic control threshold value; updating a mean vector and a covariance matrix of the model by adopting a dynamic strategy based on real-time acquired new electric quantity data of the secondary side of the voltage transformer; and calculating a new statistic according to the updated mean vector and the covariance matrix, comparing the new statistic with a statistic control threshold value, and if the new statistic is greater than the statistic control threshold value, determining a metering error fault. According to the invention, the model parameters can be updated according to the real-time change data output by the voltage transformer, the adaptability to different metering error ranges of the voltage transformer is improved, and the detection precision is improved.

The invention discloses a TCM-mode-based Si-SiC hybrid power multi-phase staggered H-bridge converter structure and a control method thereof, according to the scheme, a three-phase staggered parallel topology of a two-phase low-frequency Si-IGBT bridge arm and a one-phase high-frequency SiC-MOSFET bridge arm is adopted, and a TCM control strategy is combined, so that zero voltage switching (ZVS) of a Si device is successfully realized, the switching loss is remarkably reduced, and the switching efficiency is improved. The system efficiency is greatly improved; and meanwhile, through pilot frequency interleaving and ripple compensation technologies, total output current ripples are greatly reduced, and optimal balance between system performance and manufacturing cost is realized while the power capacity of the converter is remarkably expanded and the dynamic response speed and the output electric energy quality are improved.

The invention relates to the technical field of battery management, in particular to a battery replacement cabinet battery real-time monitoring and scheduling method, the health state of a battery is analyzed and evaluated according to a preset algorithm model, and the health state of the battery is evaluated by comparing a comprehensive health score, an internal resistance change rate and a capacity fading rate with corresponding threshold values; and determining a corresponding processing mode based on the evaluation result, including generating and sending abnormal alarm information to the operation and maintenance terminal, or executing an adjustable charging mode according to the state of residual electric quantity of the battery, or executing a protective charging mode according to the deterioration degree of the battery, the health state of the battery is actively evaluated to accurately identify an abnormal battery, for example, the electric quantity may be not low but potential safety hazards exist, in advance, so that targeted charging scheduling can be realized. According to the invention, real-time monitoring and active protection of the health and safety state of the battery are realized, so that the operation efficiency is improved on the premise of ensuring the safety.

The invention discloses an electric vehicle charger safety waiting management method and system based on an improved sequential network. The method comprises the following steps: S1, recording vehicle remaining capacity, accessory power consumption, a thermal risk tag and service pressure; s2, dividing active units according to a queuing order and service pressure, constructing an energy consumption and heat dissipation double-layer topology, and updating a weight in real time; s3, writing the double-layer topology and the historical state into a time sequence buffer area, traversing edge weight iteration vehicle electric quantity and battery temperature, and calculating a safety window; s4, calculating the waiting time of each vehicle according to the safety window and the queuing data, and generating a risk sequence; s5, the vehicles of the same unit are locally rearranged preferentially according to the urgency degree, and a correction queue is formed after fairness and connectivity verification; and S6, intercepting the correction queue according to idle stations, completing vehicle and station mapping, and issuing a charging instruction after reachability and power verification. The method has great superiority in microscopic safety evaluation, dynamic topology increment maintenance and real-time rearrangement giving consideration to safety and fairness.

The disclosed system includes two battery packs, at least one motor, a generator subsystem, controllers, and a switch wherein the battery packs are independent of one another but can either be undergoing charging or propelling an EV separately. A controller monitors comparative charge levels of the two battery packs and at a predetermined charge-difference value triggers the switch to reverse the roles of the battery packs.