205results about How to "Improve estimation accuracy" patented technology

The present disclosure relates to systems and methods for improving the accuracy of expected error estimations in hybrid cellular and WLAN location determination. In some embodiments, the method can include providing a WLAN based location estimate and an expected error estimate for the WLAN based location estimate, providing a cellular based location estimate and an expected error estimate for the cellular based location estimate, and determining the expected error of the location determination by evaluating the consistency of the cellular based location estimate to the WLAN based location estimate. In some embodiments, the location estimate with the lower expected error can be selected as the location determination of the WLAN and cellular enabled device. In some embodiments, the consistency of the estimates can include the distance between the cellular based location estimate and the WLAN based location estimate.

The invention relates to a method for estimating attitude parameters of automatic landing of an unmanned air vehicle based on visual information, which comprises the following steps: 1) processing and calculating the motion vector and estimating the expansion center on the basis of time for monocular visual information and estimating the pitch angle according to a geometrical vanishing point model on the assumption that the unmanned air vehicle slides down along a straight line; 2) forming a sparse disparity map based on matching of characteristic points by utilization of binocular stereoscopic visual information, further estimating the depth information of a characteristic point from a UAV to the ground, and acquiring the height of the UAV relative to the ground by combination of the parameters of the pitch angle and conversion from the coordinate of a camera to the world coordinate; and 3) establishing a UAV motion model, and further improving the estimation precision of the height parameter of the UAV on the basis of Kalman filtering. The invention provides the method for estimating the attitude parameters of automatic landing of the unmanned air vehicle based on the visual information and effectively improving the reliability.

The invention belongs to the technical field of digital signal processing and provides a linear frequency-modulated parameter estimating method with high precision, low complexity, high speed and high efficiency and an implementing device thereof. The invention adopts a technical scheme that: by means of an energy barycentre interpolation estimation and Radon ambiguity transformation (RAT) based modulating frequency estimating method, the method mainly comprises the following steps of: for a given input signal s(n), calculating an ambiguity function AFs(tau, xi) of the input signal s(n); exchanging scanning straight lines xi=k tau continuously; figuring out the projection of AFs(tau, xi) on the scanning straight lines by means of Radon transformation; recording all projection values; constructing a panorama discrete spectrum; searching out the peak position of the panorama discrete spectrum; estimating the projection value of the actual peak value; obtaining the estimated value of thesignal modulating frequency; searching out the peak value spectrum of a fractional order Fourier spectrum; and figuring out the energy barycentre position of the spectrum so as to estimate the signalbarycentre frequency. The method is mainly applied to the linear modulating frequency signal parameter estimation in the digital signal processing.

The invention discloses an SOC estimation method of an automobile power lithium battery. The method comprises the steps as follows: a, the method is started; b, when he shelving time is smaller than the set time T0, a step c is entered, otherwise a step d is entered; c, an SOC value during the use stoppage of the lithium battery is taken as a current SOC value; d, a real-time power lithium battery SOC value is obtained by the aid of a relation between open-circuit voltage and the SOC, and a step g is enter; e, when the lithium battery is dynamic, a step f is entered, otherwise, the step b is returned to; f, the SOC is estimated with an Ah integral method, and preliminary correction is performed; g, a difference value of the SOC value obtained in the step d and the SOC value estimated with the Ah integral method is judged, if the difference value is smaller than a set absolute value of e, and a step i is entered, otherwise, a step h is entered; h, the obtained SOC value corrects an initial SOC value of the Ah integral method; and I, the method is finished. According to the method, the SOC is corrected from different aspects, error accumulation caused by the Ah integral method for a long time is modified, and the SOC accuracy can be improved.

A locating system for determining a position of an object comprises a transmitting station that transmits a first ID signal containing a first identifier of this transmitting station; a receiving station that receives the first ID signal, measures the intensity of the first ID signal, and extracts the first identifier; a data management unit that stores and manages the intensity in association with the first identifier, the intensity and the identifier being supplied from the receiving station; and a positioning computer that estimates the position of the transmitting station using a first correcting formula defining a relation between the intensity and the distance, based on the data stored in the data management unit.

The invention relates to an accelerometer error calibration and compensation method based on a rotary mechanism, which comprises the following steps that: an accelerator is arranged on the rotary mechanism according to a certain requirements; the relationship between the dynamic continuous output of the accelerator and the rotating angle of the rotary mechanism is obtained through the rotation of the rotary mechanism; and a least square method is used for estimating and obtaining the bias, the scale factor, the non-linear error coefficient of the scale factor, the cross-coupling error coefficient and the like of the accelerator. The method uses the rotary mechanism to estimate all error coefficients of the accelerator, and is characterized by accuracy, high efficiency, easy operation, high universality and the like. After the method estimates the error coefficients and carries out corresponding error compensation, the output precision of the accelerator can be greatly improved. The method is also applicable to the calibration of a gyroscope, and can greatly improve the precision in measuring the speed of a top.

The invention provides a multiple-target and send-receive angle estimation method of a double-base multiple-input and multiple-output radar. A receiving end collects echo signals of every receiving antenna through an analog to digital (A/D) sampling module. The collected signals passes through a matched filter group, signals corresponding to every launching channel are separated, and receiving data of a virtual array is obtained, wherein the number of array elements is MN. The receiving data is expanded and is transformed into a real number field by utilizing Unitary transformation. A covariance matrix is calculated and is disassembled by utilizing characteristic value to obtain an actual value signal subspace and an actual value signal subspace. In the end, a target DOD is obtained by utilizing Unitary ESPRIT, and a target DOA is obtained by utilizing Unitary Root-MUSIC. According to the multiple-target and send-receive angle estimation method of the double-base multiple-input and multiple-output radar, the send-receive angle is automatically paired, extra pairing operation is not needed, and cross bearing of the target is achieved by utilizing the send-receive angle of the target. The multiple-target and send-receive angle estimation method of the double-base multiple-input and multiple-output radar has the advantages of being high in estimated accuracy and low in computing complexity.

The invention discloses an estimation method for endurance mileage of an electric vehicle, which comprises the following steps: 1, collecting battery electric quantity, consumed in the corresponding path, of the electric vehicle, and counting in advance to acquire data of the battery electric quantity averagely consumed by each path; 2, acquiring a running path from the current position to the destination position through a navigation system, and acquiring data of the battery electric quantity needing to be consumed according to the data of the battery electric quantity averagely consumed by each path; 3, comparing the data of the current battery electric quantity of the electric vehicle with the data of the battery electric quantity needing to be consumed; and 4, under the condition that the data of the current battery electric quantity of the electric vehicle is greater than the data of the battery electric quantity needing to be consumed, enabling the electric vehicle to prompt the data of the surplus electric quantity after arrival; under the condition that the data of the current battery electric quantity of the electric vehicle is less than the data of the battery electric quantity needing to be consumed, enabling the electric vehicle to prompt the position information that the electric vehicle can arrive in the running path; and under the condition that the data of the current battery electric quantity of the electric vehicle is equal to the data of the battery electric quantity needing to be consumed, enabling the electric vehicle to prompt that the surplus electric quantity is 0 after arrival. The estimation method overcomes the problem of very poor accuracy of an endurance mileage estimation result in the prior art and realizes accurate prediction of the endurance mileage.

A method for estimating accurately and stably the change of forces exerted on the tire or change of contact condition with the ground of the tire and an apparatus for putting it in operation.

Prepare a tire with sensors disposed therein such that the first and the second deformation amount measurement means 11A and 11B positioned on the vehicle body side and on outside, respectively, each of which comprises a lengthy detection portion 11a made of a conductive rubber member buried in the tire tread 21 and placed in a circumferential direction of the tire and comprises of detection electrodes 11b, 11b at both ends of the detection portion; and upon computing contact length with the ground of the tire vehicle body side and on the outside, from detected resistance value of the detection portion 11a included in the means of 11A and the wheel speed and from the resistance value of 11a included in the means of 11A and the wheel speed and from the resistance value of 11a included in the means 11B and the wheel speed, respectively, the load exerted on the tire and the lateral force exerted on the tire can be estimated form the average value and the difference value, respectively of the contact length on the vehicle body side and on the outside, respectively.

There is provided a mobile positioning apparatus for performing map matching based on a pixel image. The mobile positioning apparatus comprises a position storage device which holds a position information group indicating a current position of a mobile body and likelihood information thereof as a nonparametric distribution; a movement vector estimation device which outputs a movement vector indicating a moving distance and a moving direction of the mobile body at a discrete time T and likelihood information thereof; an image database which holds a peripheral map of a range of movement of the mobile body as an image group of a resolution according to a moving resolution of the mobile body; and a pixel crossing determination device which performs map matching using the position information group and the movement vector based on the peripheral map.

The invention discloses a method for estimating a carrier frequency offset and a device thereof. The invention is used for solving the problem of low estimation precision of the carrier frequency offset in an orthogonal frequency division multiplexing system existing in the prior art. The method in the invention sets a first threshold of the frequency offset estimation range in advance. The method comprises the following steps: A. a pilot symbol of the orthogonal frequency division multiplexing system is used for obtaining an estimation value of a first relative frequency offset; B. an absolute value of the first relative frequency offset estimation value is less than the first threshold value, a second relative frequency offset estimation value is obtained through cyclic prefixes of the orthogonal frequency division multiplexing system symbol and the orthogonal frequency division multiplexing system symbol; C. the carrier frequency offset estimation value of the orthogonal frequency division multiplexing system is obtained through carrying out a weighted average to the first relative frequency offset estimation value and the second relative frequency offset estimation value. The invention is used for estimating the carrier frequency offset of the orthogonal frequency division multiplexing system and increases the estimation precision.

The invention relates to a whole vehicle mass estimation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining current driving state information ofa vehicle, wherein the current driving state information of the vehicle includes a current vehicle speed, a current accelerator pedal opening degree, a current brake pedal opening degree and a currentslope; when a preset triggering condition of whole vehicle mass estimation is met based on the current driving state information of the vehicle, acquiring current driving parameters of the vehicle; and determining a current vehicle mass estimated value according to the current driving parameters of the vehicle. By adopting the method, an error of whole vehicle mass estimation can be reduced.

An attention calling apparatus operates in the following manner. That is, eyes distribution pattern is generated from the behavior of the eyes of the vehicle driver captured by a camera in a predetermined time, and driver's condition is estimated based on the distribution pattern. Further, concentration of the driver on driving is estimated based on the comparison between the distribution pattern and the stored information of distribution pattern. When the distribution pattern indicates that the degree of concentration on driving is high, the driving operation is stored in storage in association with the concentration degree. When the operation situation fulfills a notification provision condition, driver's attention is called depending on the concentration degree.

The invention provides a method and system for inverting the ground PM 2.5 through combination of geostatistical interpolation and satellite remote sensing. The method comprises: based on a space-time kriging interpolation model and a constructed space-time variogram model, obtaining a first concentration value of the ground PM 2.5 of a to-be-inverted region; based on a constructed satellite AOD inversion model, obtaining a second concentration value of the ground PM 2.5 of the to-be-inverted region; and fusing the first and second concentration values to estimate a final concentration value of the ground PM 2.5 of the to-be-inverted region. A weight relationship is established according to the root-mean-square error of the first and second concentration values, and the first and second concentration values are fused according to the weight relationship to estimate the final concentration value of the ground PM 2.5 of the to-be-inverted region. According to the method and system, the estimation accuracy of PM 2.5 is improved in a situation that ground monitoring stations are less, and the defect that PM 2.5 cannot be estimated at the place where AOD data is lost is overcome.

The invention discloses a side slip angle estimation method and system based on robust unscented kalman filtering. The method includes the steps that a three-freedom-degree vehicle dynamics model related to a side slip angle is established, a state equation and an observation equation of an unscented kalman filter are determined according to the model, and the input quantity, the state quantity and the observation quantity are determined, wherein the input quantity comprises the front wheel rotation angle and the longitudinal accelerated speed, the state quantity comprises the side slip angle,the yaw velocity and the longitudinal vehicle speed, and the observation quantity comprises the lateral accelerated speed and the yaw velocity; the weight factor is calculated through an M estimatoralgorithm; and in combination with the weight factor, the state quantity at the current moment, the state equation and the observation equation, the side slip angle at the next moment is estimated through an unscented kalman filtering algorithm. The M estimator algorithm and the unscented kalman filtering algorithm are combined to restrain the influence caused by outliers, the robustness of the unscented kalman filtering algorithm to the outliers in observation signals is improved, and the estimation accuracy of the vehicle side slip angle is improved.

What is disclosed is a system and method for estimating a biological parameter vector for a biophysics model using reflectance measurements obtained from a reflectance-based spectral measurement system. The present method uses a semi-empirical biophysics model to describe skin properties and estimate reflectance spectra and reduces the dimensionality of the estimated and measured reflectance spectra using basis vectors for computational efficiency. A mixture of algorithms are employed to generate an initial set of parameters which, in turn, are further refined using an iterative control based technique in which the error between the parameters derived from the measured spectra are compared to the parameters calculated from the estimated spectra. These errors are then processed to generate a small delta to the initial set of parameters. The process is repeated until an error between the estimated virtual biological parameters and the measured virtual biological parameters falls to zero or is otherwise below a pre-defined threshold level.

The invention discloses a method for estimating the number of persons based on deep learning, and belongs to the population density estimation based on deep learning. According to the invention, the method comprises the steps: employing a single-column convolution neural network based on a convolution layer and a pooling layer; learning the population features through the training of a large number of samples, estimating the population density map of an input image, carrying out the integration of the density map, and achieving the estimation of the number of persons on the image. Compared with other conventional deep learning algorithm, the convolution neural network employed in the invention is simple in structure, is low in complexity, is short in training time, and is higher in estimation precision.

The invention discloses an imaging method and a device on the basis of orthogonal multi-frequency ultrasonic steady echo signal. The method uses an orthogonal frequency division multiplexing modulation type to form multi-frequency continuous baseband signals which are orthogonal with each other; the multi-frequency continuous baseband signals are modulated as multi-frequency ultrasonic continuous emission signals and sent out by an ultrasonic probe; the ultrasonic probe detects the steady echo signals which are reflected back; the steady echo signals are equivalent to the superposing signals; the received multi-frequency continuous baseband signals after modulation are orthogonally decomposed, each path of receiving signals are decomposed by the characteristic that each path of signals are orthogonal with each other, the amplitude of each interface reflection echo and the position thereof corresponding to the incident interface are calculated so as to carry out the image forming. The device of the invention comprises an ultrasonic probe, a control unit, and an operation unit, a receiving/emitting unit, a processing unit and a display unit which are respectively connected with the control unit; the ultrasonic probe is connected with the receiving/emitting unit; the processing unit is respectively connected with the receiving/emitting unit and the display unit; the method and the device of the invention has precise image forming and good anti-interference performance, and reduces the cost by adopting a single probe.

The invention provides a data-guiding channel estimation method for OFDM systems, and an implementation device thereof, which belong to the technical field of digital information transmission. The method demodulates and recovers frequency-domain data symbols at the receiving end of an OFDM system and performs channel estimation. The method comprises the steps of utilizing a frame structure to obtain initial channel estimation result, building a time-domain signal frame and the cyclic convolution of channel impulse response, demodulating frequency-domain data symbols of a current frame, and performing data-guiding channel estimation and post processing. The device comprises an initial channel estimation module, a channel estimation gating module, a cyclic convolution building block, a frequency-domain data block demodulation module, a data-guiding channel estimation module, a channel estimation post-processing module and a control module. The method and the device use hidden informationcarried by frequency-domain data sent by the OFDM system in symbol modulation, as well as initial channel estimation provided by training information, completes receiving the channel estimation of all signal frames, and can reduce complexity, improve precision and increase the utilization ratio of frequency spectrum, mobile performance and other effects.

The invention discloses an ultrasonic-assisted microphone array speech enhancement device, and relates to voice signal treatment. The ultrasonic-assisted microphone array speech enhancement device comprises an equidistant linear array, a preamplification circuit, an analog-digital conversion circuit, two ultrasonic sensors, a transmitting circuit, a receiving circuit, a position computation module and a weighted stacking module, wherein, the equidistant linear array comprises five microphones; an output end of the linear array is sequentially connected with the preamplification circuit, the analog-digital conversion circuit, data cables and the weighted stacking module; the sensors are installed on extended lines at two ends of the linear array; the transmitting circuit and the receiving circuit utilize the sensors to transmit signals, and the received signals are processed through preamplification and analog-digital conversion and then are sent to the position computation module; in addition, the position computation module acquires return wave receiving signals of the sensors for matched filtering so as to acquire the ultrasonic transit time from a target to the sensors, acquires sound source position information that is input to the weighted stacking module, calculates time-delay compensation values of channels, performs time-delay compensation and stacking on each channel receiving signal of a microphone array so as to enhance voice signals in sound source directions.

A DPF accumulation amount estimating apparatus uses an integrated PM accumulation amount estimation logic which combines the difference between an engine PM emission amount and a PM regeneration amount and a DPF differential pressure model, thereby achieving minimized influences of changes in an exhaust gas flow rate and the like with resultant improved estimation accuracy. The DPF accumulation amount estimating apparatus for estimating the accumulation amount in a DPF (diesel particulate filter) provided therewith for removing PM (particulates (particulate matters)) in an exhaust gas, and includes a PM emission amount model in which a PM emission amount is set on the basis of the operating condition of an engine, a PM regeneration amount model in which a PM regeneration amount is set on the basis of the temperature difference between an outlet temperature and an inlet temperature of the DPF, and a DPF differential pressure model in which a PM accumulation amount is set on the basis of the differential pressure between an exhaust gas flow rate and the DPF, wherein the estimated PM accumulation amount of the DPF is calculated by adding a corrected PM accumulation amount obtained by correcting the estimated value of the DPF differential pressure model by using a coefficient K, which is determined on the basis of an engine speed and the fuel injection amount of an engine, to a difference between a PM emission amount and a PM regeneration amount.

Provided is a control apparatus for an internal combustion engine which is capable of estimating a single composition concentration based on an air-fuel ratio correction amount obtained by using an output of an air-fuel ratio sensor in exhaust gas and optimizing a fuel injection amount by using a concentration estimation value. When fueling is performed again during alcohol concentration change after the fueling, an alcohol concentration estimation period or a start determination period for the alcohol concentration change is extended by an integrated fuel injection amount from initial fueling until refueling, whereby alcohol concentration estimation accuracy is improved with respect to the alcohol concentration change due to the initial fueling and the refueling.

The invention discloses a construction method of a novel triple band vegetation index suitable for the estimation of a wheat leaf area index. The method comprises the following steps: normatively collecting the canopy reflectivity and leaf area index of wheat; based on a normalized vegetation index, establishing a novel triple band vegetation index form, using modeling data, adopting a random combination mode to determine optimal wavelengths and coefficients (k) of triple bands, obtaining an optimal triple band vegetation index suitable for estimating the wheat leaf area, and based on the optimal triple band vegetation index, establishing a wheat leaf area index estimating model. Independent experimental data is adopted to testify and verify the novel vegetation index and the estimating model. The constructed novel vegetation index has a simple structure; the established estimating model has high precision on estimating the wheat leaf index; and the saturation phenomenon is effectivelyavoided, when a crop leaf area index is high. The established estimating model can accurately estimate the leaf area index in real time without any loss in wheat production.

The invention relates to an RGB-D visual-odometer method based on Census transformation and local-graph optimization. The method includes the following steps: acquiring color and depth image information of an environment through an RGB-D sensor, and using color images to calculate Census description graphs; using a direct method to carry out motion estimation on a current frame on the basis of a Census description graph, and calculating a relative pose of the current frame and a newest key frame in local graphs; for points, of which gradient information is significant but depth information islacking, in the local graphs, carrying out depth tracking estimation in the current frame; and generating a new key frame according to a pose estimation result of the current frame, inserting the sameinto the local graphs, and carrying out graph optimization and key-frame management operations on the local graphs. According to the method, the Census description graphs are used for direct-method motion estimation, optimization and management of the local graphs are combined, and real-time robustness of a visual odometer in color-image brightness changing and depth-image depth information deficiency is improved.

The invention discloses a power supply management system for an exoskeleton robot. The power supply management system comprises a battery pack, a circuit protection module, a power supply conditioning module, a safety isolation module, a parameter detection module, a battery protection module and a communication interface module. The fluctuation voltage output by the battery is converted into stable electric energy by the power supply conditioning circuit, wherein the stable electric energy satisfies voltage, power and other power supply requirements of a control system, a sensing system and a driving system; the state information of the voltage, current, power consumption/temperature and the like of each system module of the exoskeleton robot is monitored in real time by the parameter detection module; through overtemperature, overcurrent and overdischarge emergency treatment, the state parameters of each system module are displayed through an upper computer monitoring platform; and the safety isolation measures, such as circuit protection, battery protection, signal isolation, noise isolation and the like are adopted in the power supply safety aspect.

When a particular selection condition is satisfied, a no-load voltage calculation section (105) calculates a no-load voltage Vsep which is a voltage piece when the current in the approximate straight line obtained by statistical processing is zero for a plurality of set data consisting of current data I(n) and voltage data V(n). Moreover, when a particular current condition is satisfied continuously for a certain time, a release voltage calculation section (106) calculates the terminal voltage of the secondary cell as a release voltage Voc. By using a preset voltage change amount adjustment constant DeltaVbc, an adjustment coefficient Kb, an electromotive force change constant Keq, and a polarization voltage generation constant Kpol, an estimated charge/discharge electricity amount calculation section (114) calculates an estimated charge/discharge electricity amount DeltaQe as a function of a no-load voltage in a predetermined period or a release voltage change amount DeltaVb.

The invention discloses a fast time-varying channel estimation method based on a simplified basis expansion model and mainly solves the problems of low estimated accuracy and high computation complexity of the existing technology. The method comprises the following implementation steps of 1) computing a matrix of a pilot symbol in a transform domain through a local pilot symbol; 2) obtaining a basis function matrix and a frequency domain matrix of a basis function based on a complex exponential basis expansion model; 3) carrying out fast Fourier transform on a receiving signal to obtain a frequency domain receiving signal and extracting a block-type pilot symbol from the receiving signal; 4) utilizing the received pilot symbol, the matrix of the transform domain in 1) and the frequency domain matrix in 2) to estimate a basis coefficient; 5) utilizing the basis coefficient to fit a time domain channel response matrix; and 6) utilizing a simplified time domain-frequency domain transformation formula to transform the time domain channel response matrix into a frequency domain channel response matrix. The method has the advantages of high estimated accuracy and low computation complexity and is suitable for an SC-FDMA system of the fixed block-type pilot.

The invention relates to the field of image processing. An embodiment of the present invention provides a head posture estimation method and a machine-readable storage medium. The head posture estimation method comprises the following steps: acquiring a tricolor color image and a depth image to be subjected to the head posture estimation; extracting a face region from the three primary color images, and generating a face gray image corresponding to the three primary color images and a face depth image corresponding to the depth image based on the extracted face region; extracting a face contour image corresponding to the face gray image; and inputting the face gray image, the face contour image and the face depth image to a head pose estimation model to output a head pose estimation resultfrom the head pose estimation model. Thus, the head pose estimation based on a single face image can be realized, and high estimation accuracy and efficiency can be ensured.

The invention discloses a registering method of a breast dynamic contrast-enhanced magnetic resonance image (DCE-MRI) sequence. The registering method comprises the following steps of: (1) reading image data of all time frames on the same layer of the DCE-MRI sequence; (2) coarsely registering an image to be enhanced and an enhanced image to obtain an initial estimation value of a deformation field; (3) performing motion compensation on the DCE-MRI sequence, and calculating an enhancement field of each time point; (4) modeling, and solving a time sequence enhancement field; (5) de-enhancing the DCE-MRI sequence; (6) solving the deformation field; and (7) judging whether the solutions of the time sequence enhancement field and the deformation field converge or not; if the solutions do not converge, regarding the currently solved deformation field as the currently estimated deformation field, and performing the step (3); and if the solutions converge, registering the image sequence. The registering method is accurate in registering and small in calculation amount; the time sequence enhancement field can be estimated.

The invention relates to a battery capacity evaluation method. When a system is powered on, a power-on capacity estimating module estimates the power-on initial capacity of a batter according to a detected single battery open circuit voltage value and by inquiring the capacity ratio, corresponding to the open circuit voltage, in an open circuit voltage meter; capacity of the battery is calculated through the current integration method when the battery is charged or discharged in the last stage of a non-discharging period, and meanwhile the module automatically conducts capacity correction on the temperature characteristic of the battery capacity according to a temperature departure linear correction table, knows the ratio of the capacity at the current temperature to the full capacity by inquiring the temperature departure linear correction table, and calculates the modified value of the current capacity; in the last stage of a discharging period, the battery capacity estimating module estimates the capacity of the battery in the last stage of the discharging period by inquiring a residual capacity table; in the last stage of the charging period, the full capacity is renewed according to the current value at present and the capacity value at present. According to the battery capacity evaluation method, the charging and discharging characteristics of the battery are taken into full consideration at different temperatures and different magnitudes of multiplying power, the capacity of the battery is estimated through the current integration method and the data table inquiring method, and calculation accuracy is improved.