290results about How to "Simplify the solution process" patented technology

The invention discloses an interior noise analysis and prediction method of a high speed train. The method comprises the following steps: establishing a train reconditioning train body model, a statistical energy analysis model of a body in white structure and an interior and exterior vocal cavity statistical energy analysis model, and carrying out simplification and subsystem division; obtaining the statistical energy analysis parameters of the train body structure and an interior vocal cavity model, and loading the statistical energy analysis parameters onto a train body structure model plate subsystem and a vocal cavity model subsystem; and obtaining exterior vocal excitation source energy borne on the train body, applying the exterior vocal excitation source energy onto the exterior vocal cavity statistical energy analysis model, causing the exterior vocal excitation source energy to reach an interior vocal cavity after the exterior vocal excitation source energy is attenuated by the sound insulation property of a structural plate in a body in white structure model so as to obtain structural noise energy radiated into the train by the reconditioning train body under the function of the two-line suspension force of a compartment, and then, carrying out interior noise analysis and prediction. The problem that the interior noise of the train is difficult in prediction and the problems of the upper limit boundedness of a frequency domain, complex calculation flow, incomplete motivation consideration in the traditional method are overcome, calculation efficiency and prediction accuracy are improved, and development and test cost is lowered.

The invention discloses a five-axis linkage machine tool rotation shaft geometric error continuous measurement method. The method comprises the steps that a laser displacement sensor is arranged on a spindle of a five-axis linkage machine tool; three non-collinear calibration balls are arranged on the work bench, and the homogeneous coordinate expression of each calibration ball is set; a swing axis A and a rotary axis C are used as calibration axes; the laser displacement sensor is used to measure the position deviation of the center of each calibration ball in X , Y and Z directions when the swing axis A and the rotary axis C in different corners; and according to the position deviation of the center of each calibration ball and the homogeneous coordinate expression of each calibration ball, geometric errors of the swing axis A and the rotary axis C are calculated. According to the invention, an oblique surface is used to establish the mapping relationship among the position deviation of a rigid body to be measured in X, Y and Z directions; translation in X, Y and Z dimensions is mapped to distance change in a single dimension; one-time chucking and continuous sampling are realized at the same time; and the method has the advantages of high measurement efficiency and high precision.

The invention discloses a method for uniquely solving the inverse kinematics numerical value of the joint type mechanical arm, belongs to the technical field of modern intelligent manufacturing, relates to the technical field of industrial robots, relates to a method for uniquely solving the inverse kinematics numerical value of a joint type six-degree-of-freedom mechanical arm with shoulder joints facing forward. According to the method, a mechanical arm joint coordinate system is built according to an improved DH parameter method, four structural geometrical parameters between adjacent joints of the mechanical arm are determined, a homogeneous coordinate transformation matrix of two adjacent coordinate systems is calculated. For a given pose matrix of a tail end coordinate system O6, animproved newton iteration method, namely a Levenberg marquardt iterative algorithm is adopted, the inverse kinematics solution of the joint coordinate system is calculated by using a jacobian matrix J, and the six joint rotation angle values theta i which correspond to the pose matrix and meet the precision requirement are obtained. The method overcomes the requirement that a traditional newton iteration method needs to fully rank the jacobian matrix j, the modeling method is simple, clear and effective, the method has the characteristics of being high in solving precision, high in solving speed and simple and feasible in solving process.

Provided is a solar cell including: a first electrode; an electron transport layer positioned on the first electrode; a light absorber; a hole transport layer; and a second electrode, wherein the light absorber contains a solid-solution of at least two organic-metal halides with a perovskite structure, having different compositions from each other.

The invention discloses a method for simultaneous localization and mapping of a mobile robot based on an improved particle filter. The method comprises the following steps: initializing an initial-moment pose of a robot; obtaining a t-moment prior probability density function according to the pose information at a t-1 moment, and generating a sampling particle set p; initializing the weights of particles; selecting an importance probability density function, generating a new sampling particle set q, calculating the weights of particles, updating the weights of the particles, and normalizing the weights; calculating the weighted sum of random sample particles at current moment t to express posterior probability density, and obtaining the moving pose and environmental map information; judging whether a new observed value is input; if so, returning; otherwise, ending the cycle; before returning, judging whether resampling is needed or not. According to the difference of the system state, a dynamic threshold is set for judgment, and a genetic algorithm is combined. According to the method disclosed by the invention, influence of a problem of particle degeneration on SLAM is reduced, and the calculated amount of the SLAM problem is reduced.

The invention provides a dynamics performance parameter optimizing method of a high-speed train, relates to the field of parameter design optimizing based on the dynamics simulation analysis of the high-speed train, and aims at effectively replacing a dynamics simulation model of the high-speed train by a comprehensive target neural network agent model and combining the design analysis and the multi-target optimization algorithm of the high-speed train in the multi-disciplinary field to analyze and optimize the dynamics simulation approximation model of the high-speed train. The method specifically comprises the steps of building a multi-rigidity dynamics simulation model for the high-speed train; determining related important input / output design spaces; selecting sampling strategy to obtain a design space sample set suitable for the dynamics performance analysis of the high-speed train; improving the generalization accuracy of the comprehensive target neural network by the bayesian regularization method; adjusting the number of nodes in a hidden layer to build the comprehensive target neural network agent network model of which the error is controlled to be within a certain of range; performing multi-target optimization through the intelligent differential evolution algorithm by using the improved comprehensive target neural network agent network model to obtain the optimized high-speed train design parameters. The method is mainly applied to the dynamics analysis and design optimization of the high-speed train.

The invention discloses a quasi-three dimensional reconstruction method for acquiring two-dimensional videos of static scenes, which belongs to the field of computer vision three-dimensional video reconstruction. The method comprises the following steps: step A, extracting double-viewpoint image pairs from each frame of a two-dimensional video; step B, respectively and polarly correcting each double-viewpoint image; step C, adopting a binocular stereo matching method based on overall optimization to respectively solve overall optimum disparity maps of all the polarly corrected double-viewpoint images; step D, reversely correcting the overall optimum disparity maps so as to obtain the corresponding disparity maps of all the frames in the three-dimensional video; step E, splicing the disparity maps obtained in the step D according to a corresponding video frame sequence to form a disparity map sequence, and optimizing the disparity map sequence; and step F, combining all the extracted video frames and the corresponding disparity maps, adopting a depth image based rendering (DIBR) method to recover virtual viewpoint images, and splicing the virtual viewpoint images into a virtual viewpoint video. The method is low in computational complexity, simple and practicable.

The invention discloses a system for distributing loads among plants of cascade hydropower stations in real time and an implementation method of the system and mainly solves the problem that under the situation that a total power generation load instruction fluctuates frequently, the water level of a counter regulation power station reservoir cannot be controlled effectively to realize real-time coordinated operation of a cascade hydropower station group in the prior art. The system comprises a strategy library, a database server, a monitoring module, a strategy and model calculating module, a data transmission module, a fault alarm processing module and a prediction calculating module, wherein the prediction calculating module, the fault alarm processing module, the strategy and model calculating module and the data transmission module are respectively connected with the monitoring module. The strategy library is connected with the strategy and model calculating module. The database server is connected with the data transmission module. The system has the advantages that later effects of real-time distribution results of the loads among plants are considered, effectively scheduling of the cascade hydropower station group is achieved, and high practical and popularization values are achieved.

The invention relates to the field of inverse kinematics of mechanical arms, in particular to a quick and simple method for solving inverse kinematics of a six-degree-of-freedom mechanical arm. A coordinate of an intersection of three rear joint shafts is determined according to the position and a posture matrix of the tail end of the mechanical arm; angles which three front joint shafts rotate by are solved in a geometrical method; the angles which the three rear joint shafts rotate by are solved according to an Euler angle transformation matrix. The concept put forward in the method can be applied to six-degree-of-freedom mechanical arms which have different geometrical structures but belong to the same type. According to the method, the solving process of the inverse kinematics of the mechanical arm is greatly simplified, the solving speed of the inverse kinematics is improved, and requirements for quickness and accuracy in the real-time control of the industrial mechanism arm can be met.

The invention relates to a nearest neighbor object tracking method based on trace point quality evaluation, belongs to the technical field of radar target tracking, and particularly relates to an object tracking method based on multiple-evaluation-index information fusion of entropy weight. The invention puts forward a method for improving the degree of nearest neighbor correlation based on comprehensive evaluation of multiple features of the trace point. In data correlation, four measurement indexes of a trace point dropping into a wave gate, including position, amplitude, Doppler and work frequency, are taken into comprehensive consideration, evaluation values under the indexes are obtained by referring to predicted values or prior information, weight values are determined by an entropy weight method so as to obtain a comprehensive evaluation value, and the optimal measurement in quality evaluation instead of the measurement nearest to a predication point in a traditional method is used as track update. Therefore, the sensor information utilization rate is improved, and the performance of weak target tracking under complex environments is improved.

The invention relates to a method for estimating pavement peak attachment coefficients of a distributed driving electric vehicle. The method comprises the following steps of: acquiring a driving force signal, a longitudinal vehicle speed signal, a vehicle-mounted longitudinal acceleration sensor signal, and a wheel speed signal; estimating slip rate and utilization attachment coefficients in real time respectively by using the longitudinal dynamics and tire dynamics of the vehicle; transmitting an estimated slip rate value to a simplified tire model, so as to obtain utilization attachment coefficient estimation values of a group of different pavements; and comparing the utilization attachment coefficient estimation values with the utilization attachment coefficients of pavements, selecting a value with the minimum error, and solving a peak value by using the simplified tire model, so as to obtain the peak attachment coefficients. The method is simple in solving process, quick in operation, short in convergence time, high in robustness, and applicable to real-time estimation of the peak attachment coefficients of the various pavements in the running process of the vehicle.

The invention provides a super capacitor, comprising: a bottom electrode, made of metal that has a sponge-like porous bicontinuous structure wherein the porous bicontinuous structure comprises a plurality of continuous nano pores; a dielectric layer, made of material with high dielectric constant and disposed on the bottom electrode wherein the dielectric layer has a thickness of 0.5˜15 nm; and a top electrode, comprising single layer or multiple layers of conductive layers and having a thickness more than 10 nm.

The invention relates to the technical field of wind power prediction, and discloses a wind power short-term prediction method. The method uses wind speed as an input, adopts a regression model of a least square support vector machine to predict output power of a wind power plant, and parameters of the regression model of the least square support vector machine are optimized by adoption of a chaotic particle swarm algorithm. The wind power short-term prediction method provided by the invention introduces chaotic motion characteristics into an iterative process, uses ergodicity of chaotic motion to improve a global searching capability of the algorithm in a searching process, overcomes the defects that the particle swarm algorithm is easy to fall into a local extreme point and is slow in convergence and low in precision in a later period of evolution, effectively solves the problem of prematurity of the particle swarm algorithm, can ensure global optimum, and achieves a better prediction effect; the method uses the least square support vector machine to predict, avoids the problem of solving quadratic programming, converts the prediction problem to a process of solving a linear equation set, and the solving process is greatly simplified; and the method adopts single wind speed as input data, and thus a prediction model is simpler.

It is an object to provide a high ion conductive solid electrolyte which uses organic and inorganic complex compound having water absorption and water resistance and to provide an electrochemical system using the high ion conductive solid electrolyte. The high ion conductive solid electrolyte is composed of a complex compound including water that has zirconic acid compound and polyvinyl alcohol. An aqueous solution in which zirconium salt or oxyzirconnium salt and polyvinyl alcohol are dissolved is neutralized by alkali. After removing water used as solvent, unnecessary salts are removed from the neutralized solution. The high ion conductive solid electrolyte is obtained which is composed of the complex compound having zirconic acid compound, polyvinyl alcohol, and water. Various electrochemical systems are obtained each of which use the high ion conductive solid electrolyte.

The invention relates to an electromechanical device nonlinear failure prediction method, comprising the following steps: 1, obtain data which can represent the running state of a device and select a section continuous vibration signal which has a long course and is sensitive to the failure to analyze; 2, respectively carry out exceptional value elimination and missing data filling to the vibration data by a 3 sigma method and an interpolation method; 3, carry out noise reduction to the vibration signal by a lifting wavelet method; 4, decompose the vibration signal after the noise reduction to corresponding characteristic bandwidths; 5, obtain a low dimension manifold character by utilizing a typical predicted characteristic bandwidth and adopting a nonlinear manifold learning method through decoupling of topological mapping and non-failure energy information; 6, carry out intelligent failure prediction with long course trend in a time domain by utilizing a recurrent neural network which has the dynamic self-adaptive characteristic and a first dimension of the low dimension manifold character as a neural network input. The lifting wavelet method is adopted in the invention, the algorithm is simple, the arithmetic speed is high, and the used memory is less, thereby being suitable for the characteristic bandwidth abstraction of failure character. The electromechanical device nonlinear failure prediction method can be widely applied to the failure prediction of all kinds of electromechanical devices.

The invention discloses a structure robustness optimization design method containing interval parameter uncertainty. The method comprises the following steps that a structure robustness optimization design model based on an internal is built; sample points are obtained by adopting a Latin hypercube sampling and co-simulating technique; a Kriging proxy model for predicting a target function and a constraint function is constructed; an interval robustness optimization design model is solved by adopting a double layer-nested genetic algorithm, left boundaries and right boundaries of the target function and the constraint function are calculated in the inner layer of the genetic algorithm, and in the outer layer of the genetic algorithm, total interval constraint violation degree vectors of all design vectors are calculated, and the feasibility of the total interval constraint violation degree vectors is judged; all the design vectors are subjected to advantage and disadvantage sorting according to a superior relationship criterion based on the interval constraint violation degree vectors; when a largest evolution algebra or convergence threshold value is achieved, the optimal solution of the robustness optimization design model is output, and the structure robustness optimization design containing interval parameter uncertainty is achieved.

The invention discloses a method for solving the equivalent impedance frequency characteristic of an HVDC transmission system converter under various operating conditions and failure conditions, whichcomprises the following steps: according to the fundamental component of voltage between phases of converting buses and the DC component of direct current, and a trigger angle instruction of a DC control system, calculating the actual trigger angle of each converting valve and the delay angle of flow of the converting valve in the converter, and the actual phase-change angle when two phases are converted; then calculating a three-phase voltage switching function and a three-phase current switching function; and by the subharmonic components of the three-phase voltage switching function and the three-phase current switching function, and the equivalent harmonic impedance of an AC network and a DC network, calculating the equivalent harmonic impedances at the AC side and the DC side of theconverter. The method can realize the calculation of the equivalent harmonic impedances at the AC side and the DC side of the converter under various AC operating conditions and failure conditions, reduce the calculation amount and meet the demand on precision in engineering application.

The invention relates to a mechanical arm tail-end pose error correction method based on elliptic characteristics. The method comprises the steps of obtaining an image of a round-mouth target tank, extracting a target ellipse from the image, determining the relative position and axial relation between a tank mouth of the round-mouth target tank and an actuator according to the elliptic characteristics of the target ellipse, determining a current pose of the actuator, joint angles of all joints of a mechanical arm and the pose deviation value of the actuator according to the relative positions,the axial relation and configuration constraint of the mechanical arm, and adjusting the mechanical arm according to the pose deviation value till the pose deviation value of the actuator is smallerthan a preset value. By means of the method, the problems that single elliptic characteristic positioning has ambiguity and axial rotation poses cannot be determined are solved, accurate guidance canbe provided for the mechanical arm to collect samples and put the samples into the target tank, and control errors caused by local flexibility or joint clearance are corrected. The invention further provides a mechanical arm tail-end pose error correction system based on the elliptic characteristics.

A dynamic non-rigid body three-dimensional digital method fusing RGB-D camera and color photometric stereo method employs an RGB tricolor light source to irradiate an object under test, and employs a depth camera and a color camera with internal parameters calibrated to photograph the object to acquire a depth image and a color image of the object; the method then estimates light source direction and reflectivity in conjunction with depth and color information; a cost function fusing a depth item, a normal item and a smooth constraint item is constructed by variational method, and an improved-quality surface three-dimensional digital model of the object under test is solved by least squares optimization. By using the method, it is possible to effectively solve the problem that an existing dynamic non-rigid body three-dimensional digital method has matching difficulty in non-rigid body objects in different inter-frame images, has great geometric error or has poor smoothness and poor detail fineness of reconstruction results due to noise impact; the method has the advantages of high efficiency, high precision and low cost, and is applicable to a three-dimensional digital task for a dynamic non-rigid object to provide efficient and convenient object three-dimensional reconstruction.

The invention provides a road surface attachment coefficient and road surface gradient synchronous real-time estimation system and method for a hub-motor-driven vehicle. The road surface attachment coefficient and road surface gradient synchronous real-time estimation system comprises a wheel trackslip rate calculating module, a wheel side-slip angle calculating module, a wheel vertical force calculating module, a Dugoff tire model module for deformation treatment, an air resistance calculating module, a fading memory UKF parameter estimation algorithm module, a wheel longitudinal lateral force calculating module, a wheel rotating dynamics module and a longitudinal force feedback and correction module. According to the road surface attachment coefficient and road surface gradient synchronous real-time estimation method, through fading memory weighting processing on a traditional UKF algorithm, obsolete measured data of the algorithm are rejected in time, the weight of newly measured data is increased, and accordingly the estimation precision of parameters is improved; and the advantage that the torque of all wheels of the hub-motor-driven vehicle can be measured precisely is fullycombined, and accurate wheel longitudinal force information obtained by the wheel rotating dynamics module is utilized to correct wheel longitudinal force information obtained by a Dugoff tire model,so that the accuracy of longitudinal normalized force is ensured, and accordingly the estimation precision of the road surface attachment coefficient is improved indirectly.

The invention discloses an antenna selection method aiming at energy effectiveness of a Massive MIMO (Multiple Input Multiple Output) communication system. The antenna selection method comprises the steps of: firstly, determining a large-scale fading factor of each user, selecting an optimal large-scale fading factor from the large-scale fading factors, and then determining an optimal number of sending antennas and a corresponding sub-collection. Based on comprehensive consideration on the power consumption of a transmit-receive end, an antenna selection method for optimal Massive MIMO energy efficiency is provided through analysis, so that the energy efficiency of the Massive MIMO system is improved greatly; when the number of the antennas in a base station is far greater than the number of servable terminals, the provided pre-coding matrix changes an expression of a channel capacity from a logarithm determinant form into an addition logarithm form, so that the resolution problem of the energy efficiency is simplified extremely; for each parameter of the energy efficiency, the number of the antenna on the transmitting end and the servable movable terminal sub-collection are subjected to distribution optimization which is equivalent to combined optimization, so that calculation complexity of the Massive MIMO system is reduced greatly.

The invention discloses a structural performance optimum design method under non-probability conditions. The method comprises following steps: an interval optimum design model considering structural reliability requirements is established; sample points are obtained by means of Latin hypercube sampling and collaborative simulation; a Kriging surrogate model for predicting objective functions and constraint functions is established; the interval optimum design model is solved by means of a double-layer nested genetic algorithm, wherein in the inner layer of the genetic algorithm, the left and right boundary of the interval values of the objective functions and the constraint functions are calculated, in the outer layer of the genetic algorithm, the interval reliability and reliability violation degree of each constraint function according to an unified formula are calculated to obtain the total reliability violation degree of a design vector, and the feasibility is determined; superiority ordering is performed on all design vectors according to a superior relation criterion based on the total reliability violation degree; the optimal solution of the interval optimum design model is output when maximum evolution algebra or convergence threshold is reached. By means of the method, structural performance optimum design method under non-probability conditions can be realized.

The invention relates to an external parameter calibration method for a camera and laser radar combined sensor, which comprises the following steps of: aligning the combined sensor to a calibration device, and performing primary scanning to obtain a first coordinate of the calibration device in a laser radar coordinate system, a second coordinate of the calibration device in an image coordinate system and a third coordinate of the calibration device in a camera coordinate system; obtaining a first transformation matrix from a calibration device coordinate system to the laser radar coordinate system through the first coordinate and the second coordinate; obtaining a second transformation matrix from the camera coordinate system to the calibration device coordinate system through a third coordinate and the second coordinate; and obtaining an external parameter matrix from the camera coordinate system to the laser radar coordinate system through the first transformation matrix and the second transformation matrix. The method is simple and convenient to operate and simple in calculation, calibration equipment is easy to obtain, and the result precision and the optimization of the method are improved.

The invention provides a spacecraft dynamics modeling method. The method comprises the following steps of: replacing a liquid sloshing equivalent mechanical model with an equivalent pendulum, enabling a closed loop topology structure to be equivalent to an open loop tree topology structure, defining a coordinate system at a hinge joint, defining a basic contact operator, characterizing elastic displacement of a flexible body, and performing recurrent calculation on the force and speed of the flexible body; and judging whether systematic calculation on a dynamics model is a forward dynamics modeling process or a backward dynamics modeling process, correspondingly substituting the forward dynamics modeling process or the backward dynamics modeling process, and deducing a system dynamics equation. The method provided by the invention is capable of not only meeting the precise modeling requirement, but also simplifying the design process, saving a lot of workload, accelerating the spacecraft development period, realizing high-precision high-efficiency dynamics modeling of a large flexible cable antenna spacecraft, achieving modeling of a flexible multi-body system capable of calculating closed loop spacecraft configuration in a simplest mode, and saving a lot of tedious and hard works.

The invention provides a shaft interior temperature distribution semi-analytical determination method and device. The method includes: dividing a shaft into N segments, with each having interior and exterior heat transfer coefficient which is a constant; obtaining an interior-exterior energy conservation expression of each segment according to the energy conservation principle, and obtaining linear relation between the interior-exterior heat transfer coefficient of each segment and interior temperature of the shaft according to heat transfer theory; obtaining shaft interior temperature distribution segment by segment from bottom to top under the known shaft bottom conditions according to the interior-exterior energy conservation expression of each segment and the linear relation between the heat transfer coefficient and temperature.

The invention discloses a method for deterring the relation between movement characteristics and a high efficient coding mode in pixel-domain video transcoding, which comprises the following steps of: selecting a video array with the typical movement characteristics under a specific resolution factor and a coding mode having the important influence on the improvement of the transcoding quality; analyzing the column diagram of the motion vector amplitude of the typical video array video frame by video frame; traversing various coding mode combinations video frame by video frame and recording the transcoding video quality, selecting the most effective coding mode by a stepwise regression method, and then clustering and simplifying the coding mode, and finally constructing the corresponding relation model between the movement characteristics represented by the column diagram of the motion vector amplitude and the high efficient coding mode. The method provided by the invention causes that the relation between the movement characteristics and the high efficient coding mode being difficult to be determined in the first is converted into a classifier, thereby the problem is solved. In the pixel-domain video transcoding process, the relation between the movement characteristics and the high efficient coding mode determined by the invention can increase the transcoding performance.

The invention discloses a route planning method for multiple unmanned aerial vehicle cooperative tracking under multiple constraints and can help overcome a problem that unmanned aerial vehicle physics and threat / obstacle constraints are not taken into consideration in conventional multiple unmanned aerial vehicle cooperative tracking. The method is characterized in that distributed fusion rules are used for fusing local filtering estimation of an object by all unmanned aerial vehicles, and an A optimal rule is used for establishing a cost function; as for the threat / obstacle constraints, thecost function is corrected via a penalty function, a steepest descent method is used for rapidly solving an optimization problem, and flight of the unmanned aerial vehicles can be facilitated via constraints over maximum turning angles of the unmanned aerial vehicles. The method can be help effectively solve a problem of multiple unmanned aerial vehicle cooperative tracking under thread / obstacle and physics constraints, and therefore cooperative tracking of the object performed by the multiple unmanned aerial vehicles in a complex environment can be realized.

The invention belongs to the field of environmental pollution monitoring, and particularly relates to a multi-spectral back scattering type soot grain size and concentration simultaneous measuring device and a measuring method thereof. Visible light emitted from a wide-spectrum light source is emitted into a flue via an illuminating optical fiber in a reflecting type optical fiber probe, and is scattered by soot in the flue so as to form scattered light, the scattered light enters a readout optical fiber via dustproof glass with a fixed-period purging device, and is split by a light splitter, multi-spectral light intensity information of the back scattered light is acquired by a linear array CCD (charge coupled device), and a signal acquisition and data processing portion realizes modeling, inverting and monitoring. A detector of the measuring device can be integrated with the light source, angle debugging is omitted, and the measuring device has higher sensitivity according to a scattering theory. The measuring method has the advantages of simple solution procedures, fast inverting speed, stable inverting results and the like.

The invention discloses a pavement peak-value attachment coefficient estimating method on the basis of a UKF (unscented kalman filter) and a corrected Dugoff tire model. The method is characterized by comprising the following steps: collecting each sensor signal of a vehicle in real time, estimating a slip rate and a slip angle of each wheel by utilizing a longitudinal kinetic equation and a geometric coordinate relation of the model; and transmitting the estimated slip rate, vertical force, the slip angle and the like to a UKF coefficient calculation module based on the corrected Dugoff model to obtain a coefficient vector of a nonlinear system, and transmitting the vector and real-time estimated longitudinal force to a UKF pavement peak-value attachment coefficient estimation module to solve a peak-value attachment coefficient. A vehicle state observation system is used for collecting the signals in real time, so that the real-time property of the calculation is guaranteed, and the estimation accuracy on pavement situations which are not fitted is high. By utilizing the corrected Dugoff tire model and a UKF theory, the solving process is simple, the number of operation is small, the rapidness in operation is realized, and the convergence time is short. The method is good in robustness, capable of well recognizing the pavement situations of each wheel and suitable for being used for estimating the pavement peak-value attachment coefficient in real time.

The invention discloses a carry-over storage year-end fluctuating level prediction method and system. The method comprises the following steps of: 1, establishing a carry-over storage year-end fluctuating level prediction model, and storing the carry-over storage year-end fluctuating level prediction model in a model library; 2, optimizing a scheduling target through a prediction server according to the maximum total cascade energy, and calculating and selecting a corresponding carry-over storage year-end fluctuating level prediction model; and 3, calling a model solution algorithm in an algorithm library through the prediction server, solving the carry-over storage year-end fluctuating level prediction model, and obtaining the year-end fluctuating level rule. Compared with the prior art, the method has the advantages that the solution process is simple, the benefits in the later scheduling period after the carry-over storage year-end are considered, and the accuracy of the prediction method can be improved; and compared with a BP neural network and other methods, the method is suitable for a reservoir with short runoff data series.