36 results about "Battery scheduling" patented technology

The invention provides a dispatching management system and method for an EMS deep fusion electric ship battery, and relates to the technical field of electric energy management, and the method comprises the steps: building a digital twin based on the state information of the electric ship battery, and obtaining a health attenuation coefficient; acquiring an abnormal fluctuation sequence of the temperature, and performing dynamic boundary division on the health attenuation coefficient through the abnormal fluctuation sequence to obtain a dynamic safety boundary; grading and limiting the output power of the battery according to the dynamic safety boundary to obtain a power regulation and control parameter set, and carrying out joint modeling on the power regulation and control parameter set to obtain an out-of-limit penalty term; performing subnet partition reconstruction on the power grid topological structure to obtain an electrical collaboration graph, and performing multi-target optimization scheduling on the electrical collaboration graph through an out-of-limit penalty term to obtain a scheduling strategy vector; according to the method and the device, dynamic electric energy optimal scheduling based on health perception can be realized, so that the stability of electric ship battery scheduling is improved.

The invention discloses a ship main propulsion intelligent control system based on multi-source data fusion, and relates to the technical field of ship main propulsion intelligent control. The problems that in the prior art, dynamic optimization is insufficient, the data fusion capacity is weak, energy efficiency is low, a fault-tolerant mechanism is passive, a control strategy is rigid, fault recovery is slow, the intelligent level is low, and complex environment changes cannot be handled are solved. According to the invention, by introducing a multi-source data fusion intelligent control algorithm, power distribution and battery scheduling of the ship main propulsion system are dynamically optimized, deep fusion is carried out in combination with environment data and equipment data, and the propulsion efficiency and energy management are improved; through multi-dimensional data fusion, system adaptability and fault-tolerant capability are improved, real-time adjustment and intelligent prediction are realized, fuel consumption is reduced, battery aging is reduced, and navigation stability is improved. The system further has an intelligent fault detection and prediction mechanism, manual intervention is reduced, and the fault-tolerant capability and the intelligent level of the system are improved.

The embodiment of the invention discloses a battery swap station energy optimization scheduling method, device and equipment and a storage medium, and relates to the technical field of battery swap station battery scheduling. The method comprises the following steps: acquiring parameters of an autoregressive integral moving average model according to historical battery replacement times of a battery replacement station, and constructing a battery replacement demand prediction model according to the parameters of the autoregressive integral moving average model; according to a Monte Carlo method and the power conversion demand prediction model, determining a power conversion demand prediction input value corresponding to the preset scheduling moment; and solving according to the power conversion demand prediction input value, the target function and the constraint condition through the model prediction control model to obtain a target energy scheduling strategy. Therefore, the optimal scheduling of energy and the maximum saving of the charging cost can be realized, the overstock and waste of battery inventory are reduced, the turnover rate and the utilization rate of batteries are improved, and stable energy supply is provided.

The invention discloses a battery swap station battery dispatching method, equipment and a medium, belongs to the technical field of battery swap, and aims to solve the technical problems that in each charging bin of a current battery swap station, batteries with different electric quantities are distributed imbalanced, so that the charging bins are easy to be idle, the battery swap stations are not uniformly queued, and the battery swap efficiency of a user is influenced. The method comprises the following steps: dividing each charging bin into a to-be-transferred-out bin and a to-be-transferred-in bin according to the electric quantity of a battery in each charging bin; acquiring a real-time queuing number of each battery changing station and an empty bin number of each to-be-transferred bin; determining a battery scheduling rule in each charging bin according to the real-time queuing number and the number of empty bins; and executing the battery scheduling rule through the battery transfer device. According to the method, the real-time queuing number of the battery swap station and the condition of the batteries in each charging bin are comprehensively considered, a detailed and accurate battery dispatching judgment scheme is provided, and the balance of the fully-charged batteries in each charging bin in the dispatched battery swap station is ensured.

The invention relates to a new energy automobile battery swap station battery dispatching method with a battery health detection function. The method comprises the steps of battery health detection model establishment, real-time detection and data synchronization, real-time detection and data synchronization and dispatching instruction execution and feedback. The method has remarkable advantages in the aspect of battery health detection, the battery state can be judged more accurately through multi-parameter fusion monitoring and intelligent algorithm analysis, compared with a traditional detection method, the detection accuracy is improved, potential problems can be captured in time through comprehensive analysis of multiple parameters, and after the potential problems of the battery are found in advance, the detection accuracy is improved. According to the method, corresponding maintenance measures can be taken, so that the service life of the battery is prolonged, the replacement cost of the battery is reduced, the use efficiency and economy of the battery are effectively improved, the operation of the battery replacement station can be remarkably optimized through a reasonable battery scheduling strategy, accurate scheduling can be performed according to user requirements and battery states, and the waiting time of users is shortened.

The invention relates to the technical field of energy management, particularly provides a photovoltaic energy storage system, a control method, electronic equipment and a storage medium, and aims to solve the technical problems of high overall cost, complex system and low conversion efficiency of a photovoltaic system of a battery swap station. In order to achieve the purpose, the photovoltaic energy storage system is applied to an energy supplementing station and comprises photovoltaic equipment, a switch assembly, a plurality of batteries and a battery dispatching management module. Wherein the photovoltaic equipment is connected with the battery through the switch assembly, and the photovoltaic equipment is configured to charge the battery; the switch assembly is configured to connect or disconnect the connection between the photovoltaic equipment and the battery; the battery scheduling management module is configured to replace a battery connected to the photovoltaic device. Through the above implementation mode, the photovoltaic device can be directly connected to the battery in the energy complementing station, multiple times of conversion is not needed, the energy conversion link is reduced, the conversion efficiency and the absorption rate of the photovoltaic energy storage system are improved, the system structure is simplified, and the overall cost is low.

The invention discloses a regional battery warehouse management method and system and a storage medium thereof, and relates to the field of shared electric vehicle battery management, and the method comprises the steps: constructing a service area and a hierarchical parking point network through data driving, precisely defining a trunk area based on multi-source people flow data, customizing a minimum electric quantity threshold value, and intelligently analyzing the urgency of a battery replacement request. And implementing a cross-hub battery borrowing mechanism, and dynamically optimizing global battery resource scheduling. Through data-driven refined operation, intelligence and high efficiency of battery scheduling in the battery warehouse of the shared electric vehicle are realized, the half-way drop risk of a user is remarkably reduced, global battery resources are converted into a value chain of dynamic circulation, coexistence of resource idleness and shortage is avoided, and the service life of the battery warehouse is prolonged. The service range and the threshold value are automatically optimized by continuously analyzing mobile data, sustainable infrastructure support is provided for urban shared travel, and meanwhile operation of batteries in a whole warehouse is maximized.

The invention discloses a battery swap station battery scheduling method, system and device and a storage medium, and relates to the technical field of battery swap. The scheduling method specifically comprises the following steps: acquiring historical order data of a target battery swap station; based on the historical order data, predicting a peak time period of the target battery swap station and battery demand information in the peak time period; generating a battery demand order; pushing the battery demand order to the mobile phone client in real time; the mobile phone user selects to receive the battery demand order and carries out battery replacement service; and ending the battery replacement service, and completing expense settlement. According to the invention, battery resource distribution of the battery swap station can be optimized, and user battery swap experience and operation efficiency are improved.

The invention discloses a flexible regulation and control system and method based on distributed photovoltaic power generation, and belongs to the technical field of photovoltaic energy storage regulation and control, and the system specifically comprises a power grid cloud scheduling platform, a meteorological sensing module, a load prediction module, a photovoltaic power generation prediction module, a net load evaluation module and an energy storage distribution scheduling module. The method comprises the steps of obtaining a net load curve based on a future generating capacity curve and a future load curve, introducing a net load reference line to compare and mark a charging window and a discharging window, and decomposing the net load curve into a high-frequency component and a low-frequency component by adopting a frequency domain decomposition technology; then different battery scheduling sub-modules are introduced to respond to the high-frequency component and the low-frequency component respectively, an optimal charging and discharging instruction in a future period is formulated based on net load absolute values and battery characteristic parameters under a charging window and a discharging window, and through distributed dynamic flexible energy storage scheduling, rapid charging and discharging response is ensured, and the charging and discharging efficiency is improved. And a peak clipping and valley filling plan can be stably executed.

Disclosed according to some embodiments of the present disclosure is a method for determining a charging station, which is performed by a battery scheduling device that performs scheduling for battery operation of a moving object. The method for determining a charging station may comprise the steps of: when a specific condition is satisfied, determining, on the basis of a current location of the moving object and a state of charge (SOC) of the battery, a movement range indicating a range in which the moving object can move from the current location; determining at least one charging station present within the movement range; and determining a first charging station among the at least one charging station on the basis of predetermined preference information of a user and information related to the at least one charging station.

The invention discloses an optimization control method for a parallel DC power supply system of a large-capacity storage battery. The optimization control method comprises the following steps: S1, collecting real-time data of a battery unit and an external environment, and constructing a data set; s2, performing noise filtering, standardization processing and missing value filling on the data set, and identifying a data mode and periodic fluctuation; s3, using the adaptive cross-layer neural network model to carry out modeling on the parallel DC power supply system, and evaluating the health state of the battery in real time; s4, analyzing a causal relationship between the battery units by applying a causal inference technology, and constructing a causal inference model; s5, reversely deducing an optimal battery charging and discharging scheduling scheme by adopting a reverse modeling technology, and dynamically adjusting a battery scheduling strategy; and S6, applying a game theory and a coevolution optimization algorithm to establish a game model between the battery units to realize optimization of local charging and discharging resources. The adaptive neural network, causal inference and the like are adopted, and intelligent control over the large-capacity storage battery parallel direct-current power supply system is achieved.

The present application relates to a kind of battery scheduling method and device for multi-edge service provider scene.The method includes: in the edge computing region of interest consisting of multiple edge service providers and multiple batteries, establish an independent agent for each edge service provider, and redefine: 1) the action executed by agent to reduce the dimension of action space, and 2) the reward after executing action, to align optimization goal, i.e. reduce carbon emission and battery degradation cost.Distributed training and distributed execution strategy are used, and Q value money disturbance strategy is added, so as to isolate the training and inference of each agent, realize information protection, in addition, action conversion mechanism is designed, the defined action is converted into the actual charge and discharge operation of battery in agent, improve the overall training and execution efficiency.The present application has the ability to effectively coordinate multiple edge service providers, can realize that carbon emission is reduced by up to 60%, while maintaining privacy and controlling overhead.

The present invention belongs to the field of electric power automation and discloses a method, system, computer equipment and medium for optimizing energy storage battery scheduling plans, including: obtaining an optimal charge and discharge power reference value under an ideal state of the energy storage battery; obtaining an initial scheduling plan for the energy storage battery based on the optimal charge and discharge power reference value and a preset power reduction function; performing an SOC verification on the initial scheduling plan; when the SOC verification passes, using the current initial scheduling plan as the iteration starting point, calling a preset optimization algorithm for iterative optimization to obtain a scheduling plan for the energy storage battery; when the SOC verification fails, using the current initial scheduling plan to update the optimal charge and discharge power reference value, and repeating the above steps. This provides a preferred iteration starting point for the preset optimization algorithm, preventing the optimization algorithm from falling into the dilemma of a local optimal solution during the process of optimizing the energy storage battery scheduling plan, improving its iterative optimization efficiency, and thus achieving fast and efficient optimization of the energy storage battery scheduling plan.

The invention discloses a battery scheduling method, an electronic device, a system, a storage medium and a computer product, and relates to the technical field of vehicles, and the method specifically comprises the steps: determining a to-be-replaced first standardized battery in a hot spot region battery replacement station; a first target unmanned vehicle is determined, and the first target unmanned vehicle comprises a second standardized battery used for replacing the first standardized battery; the first target unmanned vehicle is controlled to arrive at the hot spot area battery swap station, and the second standardized battery is replaced with the first standardized battery in the hot spot area battery swap station; and controlling the first target unmanned vehicle to transport the first standardized battery to the non-hot-spot area battery swap station. By adopting the method and the device, the load balance between the hot-spot area battery swap station and the non-hot-spot area battery swap station can be balanced, the situation of area load unbalance is prevented, the overall turnover efficiency of batteries is further improved, and the idle waste of battery assets is prevented.

The invention discloses a multi-type battery charging and dispatching joint optimization method in a new energy vehicle battery replacement battery management system. An innovative dispatching strategy is designed for solving the problems that an existing battery dispatching system does not distinguish battery types and is insufficient in capacity adaptability. The method specifically comprises the following steps: (1) according to the types and electric quantity states of the batteries, dividing the batteries into four types, namely, non-electric pure-electric batteries, non-electric mixed-electric batteries, electric pure-electric batteries and electric mixed-electric batteries, and obtaining a distance matrix between each station and a transport truck and a scheduling demand of each station; (2) classifying scenes based on the four types of batteries, and calculating the maximum detachable number of each type of batteries at each station according to the scheduling requirement of each station and the capacity limitation of a transport truck and the station; and (3) setting a priority sequence of operation of the four types of batteries, and determining a next operation node accessed by the transportation truck according to the maximum loading and unloading quantity and the transportation distance of each type of batteries at the station, so as to generate a scheduling route of the truck. The method can effectively alleviate the problem of unbalanced supply and demand of the charged battery of the battery swap station, thereby improving the resource utilization efficiency of the station charging cabinet.

According to the battery management method and system for the battery-changing electric vehicle team, when the battery distribution scheme is determined for the vehicle, the influence of factors such as the vehicle load data, the actual use data of the battery and the driving habit of a driver on the endurance mileage of the battery is considered; a battery dispatching scheme can be more accurately designed for a battery-replaceable electric vehicle team, and the distribution cost and the overall energy efficiency optimization are considered.

The present application relates to the technical field of battery-swapping station dispatching. Disclosed are an in-station dispatching method and apparatus for a battery-swapping station, and a device and a storage medium. The method comprises: acquiring a preset waiting time of an electric device in a target battery-swapping station, and decision variables and a plurality of battery-swapping optimization targets of the target battery-swapping station; determining variable constraint conditions of the decision variables of the target battery-swapping station on the basis of the preset waiting time; solving the plurality of battery-swapping optimization targets by means of the variable constraint conditions and the decision variables, so as to obtain a battery charging and swapping dispatching strategy for power supply batteries in the target battery-swapping station; and performing battery charging and swapping dispatching on the power supply batteries in the target battery-swapping station by means of the battery charging and swapping dispatching strategy. By taking into account a plurality of factors, battery charging and swapping behavior dispatching of batteries in a target battery-swapping station is quickly and accurately performed, thereby improving the accuracy and flexibility of in-station battery dispatching for battery-swapping stations.

The invention relates to the technical field of battery charging and swapping station dispatching, in particular to a double-layer model collaborative optimization method and device based on battery dispatching and a vehicle path. The method comprises the following steps: determining a first solution of a first model for battery distribution between stations and a second solution of a second model for battery transfer trolley path planning between the stations, and performing optimization iteration on the solutions of the two models through a fitness function. Through an information sharing and feedback mechanism, the two models interact and are gradually optimized to obtain a globally optimal solution, and the purpose of collaborative optimization of the two models is achieved, so that the problem of supply and demand balance between charging and battery swapping stations is solved, and the user experience is further improved.

The embodiment of the invention discloses a battery scheduling method, device and equipment applied to a battery replacement cabinet and a readable medium. A specific implementation mode of the method comprises the following steps: constructing a power conversion cabinet node network; for each power conversion cabinet node, the following scheduling steps are executed: power conversion cabinet state information is generated according to power conversion cabinet basic information, historical power conversion information and power conversion cabinet real-time information; generating battery demand prediction information according to the battery replacement cabinet state information and the historical battery replacement information; performing in-cabinet battery scheduling operation on the battery replacement cabinet according to the battery replacement cabinet state information and the battery demand prediction information; according to the battery replacement cabinet node network, each piece of historical battery replacement information and each piece of historical battery demand prediction information, generating a battery scheduling amount between each cabinet; and carrying out battery scheduling on the battery changing cabinet. According to the embodiment, the sudden power utilization event in the area can be recognized early, and battery scheduling is carried out between the battery replacement cabinets, so that the power shortage duration of the battery replacement cabinets is shortened, and the full power guarantee rate in the area is improved.

The application discloses a kind of ship main propulsion intelligent control systems based on multi-source data fusion, it is related to ship main propulsion intelligent control technical field;Solve the problems that the prior art exists dynamic optimization deficiency, data fusion ability is weak, energy efficiency is low, fault-tolerant mechanism is passive, control strategy is rigid, fault recovery is slow and intelligent level is low, cannot cope with complex environmental changes;The present application introduces multi-source data fusion intelligent control algorithm, dynamically optimizes the power distribution and battery scheduling of ship main propulsion system, combines environmental data and equipment data for deep fusion, improves propulsion efficiency and energy management;Through multidimensional data fusion, improve system adaptability and fault-tolerant capability, real-time adjustment and intelligent prediction, reduce fuel consumption, reduce battery aging, improve sailing stability;The system also has intelligent fault detection and prediction mechanism, reduces manual intervention, improves fault-tolerant capability and system intelligent level.

The present invention discloses a battery scheduling method and computing device for a city bus exchange station cluster, comprising: establishing an electric bus exchange demand model according to the electric bus exchange characteristics; determining H it , where H it represents the number of battery swapping demands at battery swap station i in time period t; a day-ahead scheduling model for battery charging and discharging of battery swap station clusters is established, whose decision variables include the number of batteries C being charged at battery swap station i in time period t it and the number of batteries being discharged, D it ; According to the constraints, the day-ahead scheduling model of battery charging and discharging of the battery swap station cluster is solved, and it is found that when the scheduling cost of the battery swap station cluster is the lowest and the fitting degree between the net load of the battery swap station cluster and the green power output is the best, C it and D it The optimal solution is obtained and used as the battery scheduling solution for the battery swap station cluster.

The application provides a scheduling management system and method for EMS deep integration of an electric ship battery, relates to the technical field of electric energy management, and is based on state information of an electric ship battery to construct a digital twin and then obtain a health attenuation coefficient; an abnormal fluctuation sequence of temperature is collected, the health attenuation coefficient is dynamically boundary-divided through the abnormal fluctuation sequence, and a dynamic safety boundary is obtained; the output power of the battery is classified and limited according to the dynamic safety boundary, a power regulation parameter set is obtained, the power regulation parameter set is jointly modeled, and an out-of-limit penalty term is obtained; the power grid topology structure is subnetwork-partitioned and reconstructed, an electrical coordination graph is obtained, the electrical coordination graph is multi-objective optimization scheduled through the out-of-limit penalty term, and a scheduling strategy vector is obtained; and a scheduling protection instruction is determined according to the scheduling strategy vector and sailing information. The application can realize dynamic electric energy optimization scheduling based on health sensing to improve the stability of electric ship battery scheduling.

The invention relates to the technical field of vehicle scheduling, in particular to a battery transfer trolley scheduling method and device, equipment and a medium. The method comprises the steps that after a first array aiming at inter-station battery dispatching is obtained, vehicle data and electricity price data are determined, and the first array comprises battery dispatching data of a plurality of battery swap stations; sending the first array and the vehicle data to a vehicle scheduling model for path planning of the battery transfer vehicle to obtain a plurality of second arrays; and calculating earnings corresponding to the plurality of second arrays according to the electricity price data, and scheduling the battery transfer trolley according to the second array with the highest earnings. The rationality of a vehicle scheduling scheme matched according to the battery demand between the stations is improved, and the purposes of reducing the power utilization scheduling cost of the battery swap station and improving the income are achieved.

The invention discloses an in-station scheduling method, device and equipment for a battery swap station and a storage medium, and relates to the technical field of battery swap station scheduling, and the method comprises the steps: obtaining the preset waiting time of electric equipment in a target battery swap station, the decision variable of the target battery swap station, and a plurality of battery swap optimization targets; determining a variable constraint condition of the decision variable of the target battery swap station based on preset waiting time; solving the plurality of battery swap optimization targets through variable constraint conditions and decision variables to obtain a charging and swap scheduling strategy of a power supply battery in the target battery swap station; according to the method, the power supply battery in the target battery swap station is subjected to battery charging and swap scheduling through the battery charging and swap scheduling strategy, the battery charging and swap behaviors of the battery in the target battery swap station are rapidly and accurately scheduled by considering multiple factors, and the accuracy and flexibility of battery scheduling in the battery swap station are improved.

The invention relates to the technical field of battery management, and discloses an intelligent management method and system for a new energy battery, and the method comprises the steps: carrying out the monitoring of a driving scene and load performance of a new energy vehicle loaded with the new energy battery, and obtaining the driving scene characteristics and load performance characteristics of the new energy battery; the method comprises the following steps: acquiring operation performance data of a functional module in functional association with a new energy battery in a new energy vehicle, predicting future load pressure of the new energy battery in combination with driving scene characteristics and load performance characteristics to obtain load prediction information, performing adaptive analysis on the load prediction information according to a preset battery scheduling strategy, and determining the load pressure of the new energy battery. And a new energy battery management strategy is obtained.

The invention relates to the technical field of battery swap station battery dispatching prediction, in particular to a battery dispatching method, device and equipment used between battery charging and swap station points and a medium. The method comprises the steps of obtaining multiple groups of battery scheduling parameters, calculating demand satisfaction values of all stations of the multiple groups of battery scheduling parameters, and performing successive multiplication calculation to obtain demand satisfaction rates corresponding to the multiple groups of battery scheduling parameters, and carrying out battery scheduling processing on the first station and the second station according to the battery scheduling parameter with the highest demand satisfaction rate. The problem that the new energy automobile battery replacement cannot be met due to the fact that station battery supply and demand are not matched is solved, and the use experience of a new energy automobile user battery charging and replacing station is further improved.

The application discloses a kind of energy storage battery scheduling strategies for oil and gas drilling normal drilling operation, belong to the technical field of storage and charging, mainly solve in the normal drilling operation of oil and gas drilling, the energy storage battery imbalance of existence in the energy supply of gas generator and energy storage battery, unreasonable problem of gas generator opening time.The scheduling strategy is combined with winch operating state, energy storage battery estimated discharge capacity and energy storage battery estimated chargeable capacity, dynamically adjusts the number of gas generator opening, controls the sustained discharge capacity of energy storage battery, not only improves the gas-electric conversion efficiency of gas generator, but also guarantees the balance of energy storage battery charge and discharge, ensures the safety of gas generator and energy storage battery collaborative energy supply in the normal drilling operation of oil and gas drilling.

The application discloses a kind of based on big data's battery scheduling algorithm promotion battery utilization efficiency's method, in turn including data reporting and collection, data collection and storage, data calculation, data back, work order distribution and battery scheduling execution five steps;Through the establishment of gray model, and then using trained gray model, predict future rental, group and battery cabinet use number of people, and according to the optimized gray model guide battery allocation and scheduling, generate work order corresponding scheduling data, work order sends distance needs battery scheduling battery cabinet nearest position of first-line dispatch personnel, first-line dispatch personnel goes to the battery cabinet position specified in work order, according to the allocation of battery in battery cabinet shown by work order information and combines scheduling path and executes battery scheduling job.The application carries out real-time monitoring and calculation to battery replacement order and battery quantity in battery replacement cabinet, and optimizes scheduling to meet the needs of rider battery replacement, while improving the utilization efficiency of battery.

The invention provides a battery swap scheduling method, a battery swap station and a vehicle, and relates to the technical field of battery scheduling, and the method comprises the steps: obtaining the vehicle state of a target vehicle; predicting a battery replacement demand according to the vehicle state; determining the battery supply capability of the battery swap station according to the battery state of the battery in the battery swap station; according to the battery replacement demand and the battery supply capacity, a battery replacement scheduling strategy of the target vehicle is determined, the battery replacement scheduling strategy comprises a battery replacement sequence strategy and a battery replacement time strategy, it is guaranteed that a battery replacement station can formulate the battery replacement scheduling strategy in advance according to the state of the target vehicle, the battery replacement efficiency is improved, and battery resources are reasonably allocated.

The invention discloses a mixed use scheduling system for an electric cabinet to adapt to various charging bottom plugs, and relates to the technical field of power conversion cabinets, and the system comprises the steps: building a power conversion probability matrix of each user in different electric cabinets based on the power conversion data of an existing user; based on the battery replacement probability of each user, the use transition probability of each electric cabinet is calculated, and then which electric cabinets need to be transformed to support batteries with different charging interfaces is determined; battery scheduling is carried out according to the number of battery bins of the battery changing cabinet, the number of batteries and user requirements; after the battery replacement cabinet is transformed, a specific charging interface type is locked, and renting, returning and battery replacement rules of the batteries are adjusted, so that resource allocation optimization of the batteries and the battery replacement cabinet is ensured. According to the method, data analysis and modeling are carried out on the battery replacement behavior of the user, battery scheduling, interface compatibility and resource configuration are optimized, the optimal matching of the battery and the electric cabinet and the optimal utilization of resources can be ensured, and a better use effect and a better use prospect are brought.