209results about How to "Verify availability" patented technology

The invention discloses a design method for a distributed hydrological model by using a grid as an analog unit, which is called as ESSI for short. The design method comprises the following steps of: obtainment of a distributed parameter: converting vector data into grid data; generalization of a watershed hydrological process: establishing a universal runoff generating type for the grid; design of a runoff generating process: respectively computing the water-quantity distributing condition of each part according to different prior-period soil water conditions; design of a flow collecting process: respectively designing a Muskingum-Cunge method, a delay algorithm and a riverway segmentation Muskingum method for the flow collecting process computation of the model under different conditions; and model development and integration. The invention not only can finish the watershed hydrological process simulation at an arid region and a humid region, but also can realize the short-term flood forecast and the long-term rainfall-runoff process simulation and prediction of a watershed by using modularization and integration ideas as means, thereby providing scientific reference bases for deeply learning about the physical mechanism of water circulation by people, reducing the drought and water-logging disasters and reasonably developing and utilizing water resources.

The invention discloses a joint probability density prediction method of short-term output power of a plurality of wind power plants. The method comprises the following steps: carrying out single point value prediction on output power of each wind power plant by using a support vector machine regression prediction model; building a sparse bayesian learning model as to a prediction error to carry out probability density prediction of the error, so as to obtain an expected value and a variance of marginal probability density function prediction of the output power of a single wind power plant; carrying out statistic analysis on the prediction error characteristics of the output power of the plurality of wind power plants, building a dynamic conditional correlation-multivariate generalized autoregressive condition heteroscedasticity model, and integrating a marginal probability density prediction result of the output power of the single wind power plant and a correlation coefficient matrix to obtain a joint probability density function of the output power of the plurality of wind power plants; forming a multidimensional scene including space-time correlation characteristics by using a sampling technique. By adopting the joint probability density prediction method, a mean prediction value and prediction uncertainty information of the output power of the single wind power plant can be provided; the dynamic space-time correlation characteristics between output power prediction of the plurality of wind power plants also can be quantitatively described.

The invention provides a method for precisely editing a genome DNA sequence. A TALEN, CRISPR / Cas9 and other gene targeting technologies and homologous recombination technologies are utilized in a combined mode for precisely editing the genome DNA sequence. According to the method, the technical problem that in the prior art, a specific sequence cannot be deleted is solved, the specific base sequence can be seamlessly inserted or deleted in a fixed point mode, and seamless free modification of the genome DNA sequence of eukaryocyte is achieved for the first time.

The invention relates to the technical field of underground road bituminous pavement service performance evaluation. In order to make the evaluation result objective, the effective scientific decision can be provided for the road maintenance and repair department. In order to fulfill the aim, the adopted technical scheme is as follows: the entropy weight-based underground road bituminous pavement service performance evaluation method comprises the following steps of: 1. determining a composite underground road pavement performance integrated evaluation index system, namely 1.1. determining evaluation indexes and evaluation standards, 1.1.1. determining underground road bituminous pavement damage condition evaluation indexes and standards, 1.1.2. determining composite underground road pavement driving quality evaluation indexes and standards, and 1.1.3. determining composite underground road pavement safety performance evaluation index and standards; 1.2, establishing a comprehensive evaluation model; and 2. performing a composite underground road pavement service performance evaluation method. The method is mainly applied to the underground road bituminous pavement service performance evaluation.

A received signal strength (RSS) predictor of a propagation-free model is trained based on a large number of actual network data sets, and the coverage performance of base station (BS) deployment is optimized through a multi-target heuristic method. In particular, more practical features of signal propagation, such as geographical environment and operating parameters of a base station, are fed into a machine learning (ML) model to predict received signal strength; besides, a multi-objective greedy algorithm is designed based on the prediction model, a feasible solution is initialized to meet geographical constraints and is fixed to be related to longitude and latitude of an optimization area, the optimization step length in the search direction is fixed, the step length is set according tothe upper limit and the lower limit of parameters, and the optimization objective is that the coverage rate reaches the standard with the least base stations. Numerical simulation results show that the multi-layer perceptron is superior to other machine learning algorithms in the aspect of received signal strength prediction, convergence and availability of the method are verified through base station deployment simulation, the coverage rate is better than that of actual deployment, and the number of base stations needing to be deployed is smaller.

The invention discloses a method for carrying out well design by using time-lapse seismic, which comprises the following steps: 1) respectively obtaining seismic data of two different time points according to methods of the step a and the step b: a. detecting the stratum basic parameters of a region to be detected, manufacturing an oil deposit profile of the region to be detected, establishing a stratum profile module according to the oil deposit profile, and obtaining three data bodies: the longitudinal wave speed, the transverse wave speed and the density according to the stratum basic parameters and the stratum profile module; and b. carrying out AVO forward modeling to obtain the overlapped seismic data of each incidence angle; 2) processing the seismic data in the two times to obtain seismic data difference; 3) carrying out reversion on the seismic data difference to obtain longitudinal wave difference, transverse wave difference, density difference and longitudinal and transverse wave speed ratio difference; 4) predicting the oil deposit parameter change; and 5) carrying out well design. The invention forms the difference reversion based on the time-lapse seismic for realizing the oil deposit parameter change prediction process and determining the well design, and the goal can not be realized by using conventional methods.

The invention discloses a pedestrian dead reckoning method based on low-cost multisensor fusion, and a relevant detailed method process is disclosed so as to solve the defects of being low in accuracy, poor in hardware quality, susceptible to interference and the like of low cost sensors. A method combining EKF (extended Kalman Filter), ZUPT (Zero Velocity Update) and a magnetometer is disclosed for gait detection and velocity error correction, and by use of an accelerometer and the magnetometer for gyroscope error correction, heading angle error correction can be realized. Actual tests show that the method can well meet indoor pedestrian positioning requirements, and the positioning error accounts for about 2% of the total distance. The method can greatly reduce the error brought by the low accuracy of multi sensors by use of multisensor fusion, and can effectively improve the attitude accuracy compared with an inertial measurement unit. The method has high application prospect and value in robots, LBS (Location Basic Service), indoor pedestrian dead reckoning, and the like, and has wide practicability and generality.

The invention belongs to the technical field of wind power generation, and discloses a comprehensive control system adopting a doubly-fed wind generator participated in power grid primary frequency modulation. The control system comprises a rotor rotary speed control module, a simulation inertia control module, a droop control module, a rotary speed protection and power determination module and apitch angle control module. After the wind generator is participated in frequency modulation, the power grid inertia is equivalently enlarged, so that the doubly-fed asynchronous wind generator can have inertia response on the power grid frequent as the conventional synchronous generator, thereby lowering change rate of the power grid frequency; and by controlling the rotary speed and the pitch angle, the wind generator output is lowered, so that the wind generator has certain active backup capacity to be participated in primary frequency modulation, thereby lowering steady-state error of thefrequency.

The invention belongs to the technical field of fault diagnosis of rotary machines, and relates to a fault diagnosis method for a condition-variable planetary gear box based on multi-sensor information fusion, especially to a fault diagnosis method suitable for the condition-variable complex wind power planetary gear box. The method comprises the following steps that (1) according to the structural characteristic and diagnosis difficulty of the planetary gear box, proper vibration measuring point positions and sensor types are selected, and a collection scheme is made; (2) according to the order reconstruction technology, vibration signals are preprocessed, nonlinear non-smooth time domain signals are converted into smooth angle domain signals, and non-smooth vibration time-domain signals sampled in equal time interval are converted into angle domain vibration signals with smooth feature; (3) information of multiple sensors is fused; (4) faults of the planetary gear box are divided into distributed faults and local faults; (5) fault modes are identified; and (6) verification is carried out. According to the diagnosis method, the accuracy of a diagnosis result is high, and the practicality is high.

The invention discloses a three-dimensional core image pore and throat segmentation method and belongs to the technical field of image segmentation. The method includes: making communication marks on a three-dimensional core model; subjecting each communication area to three-dimensional distance transformation; calculating a gradient module value of transformed results; seeking key points; subjecting the found key points to framework generation; adding frameworks generated by all the communication areas to obtain a whole three-dimensional core model framework C; calculating pore-diameter cross section area of each framework point in the framework C; seeking pore seed points; subjecting the pore seed points to region growing to mark out each pore of the three-dimensional core model so as to complete three-dimensional core image pore and throat segmentation, wherein mutual contact positions among pores are throats. By the three-dimensional core image pore and throat segmentation method, problems of large errors, over-segmentation, under-segmentation and the like in traditional segmentation method can be reduced, so that three-dimensional core image pore and throat segmentation results are more accurate and effective.

The invention provides a system and a method for synchronously switching trigger timing of semiconductor valves, belonging to the field of power electronic automation. The method is realized through a set of valve control system. The valve control system comprises a master control unit, a return inspection unit and valve base electronic (VBE) units of valves. The master control unit is used to receive trigger timing switching order given by the outside and to adjust the entire timing switching process. Each VBE unit is used to verify the trigger timing selected by the master control unit and to feed back return information to the return inspection unit after check and to trigger or cut off the corresponding valve according to the selected trigger timing. The return inspection unit is used to receive the return information reported by each VBE unit and to feed back the information to the master control unit after the information is summarized. The method can satisfy the requirements of converter valve operation testing devices or other large-scale power electronic devices on the synchronous switching of valve trigger timing.

The invention discloses a method for extracting cracks in a three-dimensional rock image. The method includes the following steps: performing surface reconstruction, Laplace mesh smoothing and mesh simplification operation in sequence on each connected component of a three-dimensional rock pore model; then based on the triangular mesh unit triangle area and unit normal vector characteristics, utilizing K-mean clustering to calculate a clustering center; classifying a triangular mesh unit again according to the clustering center; executing hole repairing on a three-dimensional surface structure formed by triangular mesh units in each triangular mesh class to obtain a closed surface structure set; judging whether the closed surface structure set is a crack according to parameters such as a shape factor and an area ratio; executing morphological expansion processing on a closed surface structure set surface and internal voxel point set and performing AND operation on the closed surface structure set surface and internal voxel point set and a voxel point set of original three-dimensional rock pore model connected components, and a voxel point set obtained by the And operation is a crack. Compared with a traditional method, the method provided by the invention can correctly identify and accurately extract rock cracks.

The invention discloses a method for building a Nierji reservoir water ecological risk early warning model through the fusion technology, and relates to a method for building a Nierji reservoir water ecological risk early warning model. A system dynamics decision-making module is adopted for risk early warning and decision making quantitative analysis, then a Bayesian network model is adopted for risk early warning and decision making quantitative analysis according to a quantitative analysis result, and therefore Nierji reservoir water ecological risk early warning and decision making are achieved. The Nierji reservoir water ecological risk early warning model is built, the system dynamics and the Bayesian network model technology are fused, quantitative advantages in early-warning and decision-making research are highlighted, and Nierji reservoir water ecological risk early warning and decision making are achieved. The accuracy of the model is verified based on comparison and analysis for current data, and the availability of the model is verified through early-warning research on relative risk source risks and decision-making research on control strategies.

The invention discloses an online identification method of small-disturbance stability parameters based on PMU measurement data. The method includes: according to a linearization state matrix, with the combination of the PMU measurement data (generator angular velocity, power angle and internal potential trend data) of an electric power system, the matrix operation form of the ordinary least squares solution of to-be-estimated parameters (conductance, susceptance, and generator time constant and damping coefficient) is deduced. The beneficial effects of the method are that the current operation state can be accurately reflected through abundant measurement data, and a great help is provided for the improvement of the accuracy of practical parameters of the electric power system.

The invention discloses a strategy hiding type data access control method based on a block chain, which ensures the absolute control right of a user on data by utilizing the characteristics of decentralization, automatic execution of an intelligent contract and the like of the block chain, and avoids the risk of user privacy data leakage caused by random viewing of an access control strategy in the block chain. The homomorphic encryption thought is used for reference, the access control strategy can be correctly executed under the hidden condition through the bilinear mapping technology, and the privacy leakage risk caused by the access control strategy is prevented. The method comprises the steps that (1) a blockchain platform executes a group generation algorithm to generate common parameters; (2) a data owner generates personal related parameters through public parameters, constructs an access control strategy tree and publishes the access control strategy tree to the block chain; (3) a data accessor generates an available private key of the data accessor by utilizing the public parameters and the related parameters of the data owner; and (4) the blockchain platform firstly detects the availability of the visitor private key, then performs access control decision on the visitor private key and the data owner access control tree, interacts with the cloud storage service to complete data access if the matching succeeds, and otherwise returns rejection information.

The invention relates to a method for movie recommendation on the basis of an orthogonal and cluster pruning based improved multi-objective genetic algorithm. An improved algorithm OTNSGA-II is provided aiming at defects in distributivity and convergence of NSGA-II (non-dominated sorting genetic algorithm-II) and can be used for solving various multi-objective function optimization problems. By design of fault multi-objective orthogonal experiment initialization population, distributive deficiency caused by individual nonuniformity is avoided; by application of self-adaptive cluster pruning strategies, a population evolution process is maintained, and inferior individuals in an appropriate quantity are removed to keep convergence and distributivity of the population. By combination with information mining of user behaviors and movie properties, the algorithm is applied to solving of a practical problem of personalized movie recommendation, universality and effectiveness of the algorithm are explained by test comparison with existing algorithms, better recommendation results are obtained, recommendation accuracy rate, recall rate and coverage rate are increased, rich recommendation scheme combinations are provided, and interest points of users can be mined beneficially to provide more reliable recommendation services.

The invention discloses a polymerase chain reaction (PCR) method for detecting Brucella based on a dual priming oligonucleotide (DPO) primer, and a DPO primer sequence thereof. The method comprises the following steps of: selecting a Brucella Omp25 gene as a target gene; through BLAST analysis of the gene sequence, selecting a conserved region of the target gene sequence, and designing and synthesizing the DPO primer, wherein the nucleotide sequence of the DPO primer is as follows: BO-DPOF: 5'-CTTTTGCTGCCGACGCCATCCIIIIIAGGAACAGC-3', and BO-DPOR: 5'-TTCGTCGTCCAAGCCGTTGTTAAIIIIIGCTTGATCT-3'; and establishing a DPO-PCR detection method so as to perform precise qualitative detection on the Brucella. The invention also relates to a detection kit which has the advantages of high detection specificity, high accuracy and high sensitivity.

The invention discloses an improved NSGA-II based individuation film recommendation method. In order to overcome the defect that a traditional recommendation algorithm only has accuracy and does not have diversity, a multi-objective optimization algorithm is adopted for optimizing two objectives, and therefore the diversity is improved on the condition that the accuracy is kept. In order to overcome the defects existing in the NSGA-II multi-objective optimization algorithm, the improved algorithm FFNSGA-II is put forward, the comprehensive relative entropy is designed for filtering initialized population, and population maldistribution is avoided; the self-adaptation noninferior solution filling is applied for maintaining the population evolution process, and the population astringency and distributivity are kept. On the basis of combination of user behaviors and film attribute information mining, the algorithm is applied to the actual individuation film recommendation, the universality and effectiveness of the algorithm are illustrated through testing comparison of the improved NSGA-II based individuation film recommendation method and an existing recommendation method, the better recommendation result is obtained, and the recommendation accuracy and diversity are improved.

The invention relates to an automatic driving service unloading method based on edge calculation. The method comprises the steps of S1, enabling a vehicle with an automatic driving function to sense the surrounding environment through various sensors and obtains data; S2, querying and detecting a current network state and available resources through an API before the vehicle runs; S3, enabling theedge or the cloud to calculate unloading strategies in different network states through an ILP integer linear programming model, and store the unloading strategies as a lookup table; S4, when the vehicle runs, registering the current network state with the stored lookup table, and when the matching is unsuccessful, performing adaptive dynamic scheduling by using a heuristic algorithm, and takingthe nearest task unloading strategy in the lookup table as the reference of the heuristic algorithm for iteration; and S5, returning a calculation result to the unmanned vehicle by the edge server andthe cloud, and repeating the operation in the step S4 at the beginning of the next period. According to the method, the low-delay performance required by unmanned driving is ensured, the service quality is improved, and the response time of an automatic driving calculation task is effectively shortened.

The invention discloses a micro-surfacing mixture mineral aggregate grading optimization design method. The method comprises the following steps of 1) determining different mineral aggregate grading schemes through the throughput of key sieve holes; 2) determining the stacking density of each scheme of the different mineral aggregate grading schemes; 3) performing initial performance testing on different graded mineral aggregates; 4) determining physical and mechanical indexes of the different graded mineral aggregates; 5) performing road performance examination on the different graded mineral aggregates; 6) determining micro-surfacing mixture optimal mineral aggregate grading. According to the method disclosed by the invention, the quality of the micro-surfacing mixture mineral aggregate grading is judged by adopting an aggregate stacking density method, so that a micro-surfacing mixture with a dense framework structure is obtained; moreover, the earlier-stage and later-stage road performances of the micro-surfacing mixture are comprehensively considered, so that a micro-surfacing mixture with great high temperature stability, skid resistance and relatively high abrasion resistance is obtained. According to the design method provided by the invention, test data is accurate and reliable; by referring to a testing method for a hot-mixed asphalt mixture, the popularization value is very good.

The invention discloses an asphalt mixture aging test method. The method comprises the steps that: a short-term aging hot-mixed asphalt mixture sample is obtained with a hot-mixed asphalt mixture accelerated-aging method specified by highway engineering asphalt and asphalt mixture testing procedures; the short-term aging hot-mixed asphalt mixture sample is obtained, and a testing method and testing equipments same as those of a pressure-aging-vessel-accelerated asphalt aging test specified by the highway engineering asphalt and asphalt mixture testing procedures are adopted, and an asphalt mixture long-term aging test is carried out; the performances of the long-term aging hot-mixed asphalt mixture obtained by the test is compared with the performances of an original non-aged asphalt mixture, such that the aging degree of the hot-mixed asphalt mixture can be accurately determined. With the testing method provided by the invention, the performance aging condition of the asphalt mixture after long term use in an actual environment can be simulated, such that the aging performance or the anti-aging ability of the asphalt mixture can be accurately determined.

The invention provides a Markov model-based multi-energy complementary system random stability analysis method. In order to reasonably describe the changing condition of the illumination and the windspeed, existing illumination data, wind speed data and the like are subjected to clustering analysis, and then the center point of each cluster is obtained. The center point of each cluster is adoptedas one Markov state. A transfer rate matrix between all states is obtained through Bayesian reasoning. According to the Kirchhoff voltage and current law, a Markov state space model is built. On theabove basis, a random Lyapunov function is constructed for carrying out the random stability analysis. Moreover, though detecting the current value of a grid connection point, a current controller isdesigned to carry out the in-situ reduction of an adjustable load. According to the fluctuation condition of the new energy power generation, the consumption amount of the load is adjusted. Therefore,the power transmitted to the power grid is guaranteed to be continuous and stable. Finally, the simulation operator test is established and then the effectiveness and the practicability of the methodare verified.

Embodiments of the invention provide a database backup verification method and device. The method comprises the following steps of: obtaining to-be-verified data, wherein the to-be-verified data comprises backup data of at least one database instance; verifying the correctness of MD5 values of backup data of the at least one database instance so as to verify the integrity of the to-be-verified data; sampling and accessing the backup data of the at least one database instance so as to verify the availability of the to-be-verified data; and if both the integrity and availability pass, storing the to-be-verified data. According to the method and device provided by the embodiments of the invention, the effectiveness of the backup data can be verified so as to ensure that original data can be restored through the backup data.

The invention relates to a transformable array electrode type remediation device for heavy metal polluted soil. The device is characterized in that a soil chamber is arranged around a central electrode chamber, and the soil chamber and the central electrode chamber form concentric circles; a PRB (Permeable reactive barrier) is arranged in the concentric circles in the direction vertical to the electric field direction, and the central electrode chamber and the PRB form concentric circles; the space between the central electrode chamber and a PRB body is filled with a medium filler; six hollowvertical column type anode chambers are uniformly distributed on a circular arc of the soil chamber and are treated as surrounding electrode chambers; filtering nets are attached to the soil chamber,the anode chambers, the PRB, and the inner walls, adjacent to cathode chambers, of the PRB; electrodes are arranged in the anode chambers and the cathode chambers. According to the device, the array electrode arrangement mode is adopted, so that the remediation efficiency is improved; the remediation period is reduced; the size of the electrode chamber is adjustable; the electrodes can move, thusthe device can be switched among different remediation ranges, and as a result, the practicability is high; the electric remediation mode and the PRB are combined, so that the heavy metal in the soilcan be efficiently removed.

The invention discloses a continuous power flow method of an alternating current and direct current power system considering wind power randomness. Specific to the problem existing in stability calculation of a static voltage of a wind power plant-containing alternating current and direct current hybrid power transmission system, a Monte carlo method is adopted creatively to obtain a function relation between wind power output and voltage collapse point load margin through fitting; a calculation formula of voltage collapse point load margin expectation is deduced according to an air speed weibull distribution function, a relation between wind power output and power and a fitted function; the effectiveness of the method is verified on an improved IEEE9 node system; compared with the conventional Monte carlo method, the continuous power flow method disclosed by the invention is higher in accuracy and higher in speed; influence to the voltage collapse point load margin expectation from a direct current variable control value and air speed probability distribution parameters k, c values is further analyzed; and the method also can perform analysis on load margin of different load output directions conveniently, so that a direct current control value can be reasonably set by an operator according to the current air speed distribution condition so as to regulate an operating way favorably.

The invention discloses a method for learning surface roughness of multi-parameter parts based on a random forest. Firstly, a training sample set and a test sample of a speckle image are collected, the image is preprocessed by a Butterworth filter to perform feature researches on the speckle image, multi-feature extraction is achieved, monotonicity between features and the roughness is found, anda strong classifier is constructed based on the random forest; mutual information amount learning feature weights are introduced, and combined with correlation coefficient and random forest learning parameters, a roughness learning function is constructed; finally, the learned roughness function is used for measuring the roughness of the test sample. The method establishes a novel model of a learning process type and the roughness value, breaks through the limitation that existing methods need to establish multiple measurement roughness value models for different process parts, provides a newidea for roughness measurement, and verifies effectiveness and practicability of a new algorithm through experiments.

The invention discloses a recovering method of asphalt in an asphalt mixture. The method comprises the steps that: asphalt in asphalt mixture is extracted by using a centrifugal separation method specified by highway engineering asphalt and asphalt mixture testing procedures, such that an asphalt solution is obtained; the obtained asphalt solution is placed in a beaker and is allowed to stand for 24h for precipitation, and an upper-layer asphalt solution is obtained; the obtained asphalt solution is subjected to asphalt recovery by using an Abson method specified by the highway engineering asphalt and asphalt mixture testing procedures; the obtained recovered asphalt is placed in an aluminum spoon with a relatively large diameter, and is evaporated for 4h under a temperature of 130 DEG C in a baking oven, such that final recovered asphalt is obtained. The obtained final recovered asphalt can be used in various performance tests. With the recovering method of asphalt in asphalt mixture, the influences such as mineral powder and trichloroethylene residual solutions during the extraction and recovery processes upon the performances of asphalt can be effectively eliminated, such that the performance test accuracy of the recovered asphalt can be ensured.

The invention relates to a flat steel bifurcated pipe and a manufacturing method thereof. The flat steel bifurcated pipe comprises a main pipe, a left branch cone and a right branch cone, wherein one end of the left branch cone is communicated with one end of the main pipe; one end of the right branch cone is communicated with one end of the main pipe; one side of the left branch cone leans against and is welded with one side of the right branch cone; another end of the left branch cone and another end of the right branch cone are respectively communicated with a left branch pipe and a right branch pipe; bottoms of the main pipe, the left branch cone, the right branch cone, the left branch pipe and the right branch pipe are located at the same one altitude. The flat steel bifurcated pipe has the advantages that the shape of the flat steel bifurcated pipe is different from the principle of the same one altitude of axial lines of various pipe joints of the other steel bifurcated pipes and ensures the same one altitude on the bottom of the various pipe joints; the same one altitude on the bottom of the pipe has independent goodness; water can flow freely to be discharged when high-pressure pipes are maintained without pumping the water by a water pump or arranging holes on the steel bifurcated pipe and connecting with a special drainage system; the drainage time is shortened greatly, and the effective work time for maintenance is prolonged; the flat steel bifurcated pipe has the advantages of regular shape, no deformity portions, reasonable force and no stress concentration phenomenon.

The invention discloses a method for observing charge and discharge state of a power battery based on a variable parameter model, and belongs to the technical field of battery performance optimizationdesign. Aiming at the problems such as large errors of the existing lithium battery model and imperfect SOC observation method, a design is provided concerning the online precise observation technique of the SOC of the lithium battery, a TS fuzzy and extended Kalman filter (TS-EKF) joint estimator based on a variable parameter second-order RC model is proposed, thereby, by using the variable parameter second-order RC model, ensuring the simplicity of the model structure at the same time while ensuring good description of charge and discharge dynamic process of the lithium battery, realizing the control of grouped energy storage batteries and ensuring safe and efficient operation of the energy storage equipment. By realizing the TS-EKF joint observation algorithm on the physical platform,and at the same time, comparing the observation result of the SOC with the existing estimator, the superiority of the TS-EKF joint estimator is confirmed. The lithium battery SOC observation method provided by the invention plays an important role on maintaining safe and efficient operation of the battery system equipment, extending the overall life cycle of the battery pack and other aspects.