CN110441691A - It is a kind of based on the SOC estimation method for simplifying particle Unscented transform - Google Patents
It is a kind of based on the SOC estimation method for simplifying particle Unscented transform Download PDFInfo
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Abstract
The present invention relates to a kind of based on the SOC estimation method for simplifying particle Unscented transform, belongs to new energy measurement and control area；This method accurately estimates target for Li-ion batteries piles SOC value, by simplifying three particles and dual Sigmaization treatment process, realizes effective iterative calculation of SOC value；This method simplifies three particle Unscented transforms by carrying out on the basis of the weight coefficient of sample data sequence calculates, and realizes the simplification processing of iterative process；This method realizes the pretreatment of weight coefficient vector on the basis of weight coefficient calculates；This method, using the dual Sigmaization treatment process of the first step and the 4th step in Unscented kalman, obtains the modified computing method of influence of noise on the basis of process noise and observation noise correction analysis；This method improves the iterative process based on Unscented kalman, will simplify particle Unscented transform thought and is applied particularly to predict and modify link, realize the mathematical iterations operation of SOC value, constructs providing method reference for SOC appraising model.
Description
Technical field
The present invention relates to a kind of based on the SOC estimation method for simplifying particle Unscented transform, and this method is directed to lithium ion battery
The accurate estimation target of group SOC value, proposes one kind and simplifies particle Unscented transform method, by simplifying three particles and dual
Sigmaization treatment process realizes effective iterative calculation of Li-ion batteries piles SOC value；Particle Unscented transform method is simplified to exist
On the basis of the weight coefficient of sample data sequence calculates, three particle Unscented transforms are simplified by carrying out, realize iterative process
Simplification processing；Particle Unscented transform method is simplified on the basis of the setting that initial weight coefficient and dimension are 1, in conjunction with each power
Parameter pretreatment of the weight coefficient vector in SOC estimation is realized in the calculating of weight coefficient；Particle Unscented transform method is simplified in mistake
Journey noise and observation noise corrected Calculation analysis on the basis of, using in Unscented kalman the first step and the 4th step it is dual
Sigmaization treatment process obtains the modified computing method of influence of noise；This method is fully considering that lithium ion battery works in groups
On the basis of, the iterative process based on Unscented kalman is improved, particle Unscented transform thought will be simplified and be applied particularly to
Prediction and modification link, realize the foundation of Li-ion batteries piles SOC appraising model and the mathematical iterations operation of SOC value；This method
It is that a kind of Li-ion batteries piles based on modern control theory simplify particle Unscented transform state estimating method, belongs to new energy survey
Control field.
Background technique
In the whole life cycle of aviation Li-ion batteries piles, battery management system (Battery Management
System, BMS) effect and safety that emergency power exports will affect to the monitoring and regulation of core parameter SOC；Therefore, real
When monitor the variation of the parameter, and ensure that the working performance of Li-ion batteries piles is very important based on this；Due in BMS
SOC estimating techniques are still immature in groups, and security risk present in use process seriously constrains the development of Li-ion batteries piles；
For aviation Li-ion batteries piles, reliable BMS management relies on accurate SOC value；In the situation known to the value, not only
Reliable energy management and security control are carried out to it, but also avoid the premature deterioration of Li-ion batteries piles, extends it and uses the longevity
Life；Therefore, SOC value is accurately estimated, to the working performance and its energy and safety management for ensureing aviation Li-ion batteries piles to pass
It is important；The SOC appraising model building of Li-ion batteries piles and accurate estimated value must obtain, it has also become its energy and safety management
Key problem；Aviation Li-ion batteries piles are combined by the cobalt acid lithium battery monomer with high-energy density and closed circuit voltage and are constituted,
Its safety is influenced by locating working condition；SOC characterizes the residual capacity of aviation Li-ion batteries piles, is for aviation control
Total system processed provides emergency power and supplies key factor to be protected；In addition, the charge and discharge process of Li-ion batteries piles includes complexity
The links such as electric energy, chemical energy and thermal energy conversion, overcharge and over-discharge electrical phenomena easily cause safety accident, and accurate SOC estimation is anti-
Only play an important role in overcharge and overdischarge；In the aviation field application of Li-ion batteries piles, safety is still
The problem of paying close attention to the most, SOC estimation are basis and the premise of its safe handling；Aviation Li-ion batteries piles use battery cell grade
It is coupled structure, meets capacity and voltage requirements during auxiliary power energizes；However, due to unavoidable material and technique
Difference inconsistent phenomenon objective reality and not can avoid between monomer；Also, the phenomenon can with cycle-index increase increasingly
Obviously, expressing for inconsistency becomes the important component that SOC is estimated in groups with amendment between this allows for monomer, while also giving
SOC, which is accurately estimated, in groups brings huge challenge.
For the necessity and urgency demand of SOC estimation, related research institutes and colleges and universities, such as the Massachusetts Institute of Technology, guest
State state university, American South card university, Leeds, England university, Robert Gordon, Britain, National Renewable Energy room,
Leyden Energy Inc., the U.S., scientific & technical corporation, German Infineon, Tsinghua University, BJ University of Aeronautics & Astronautics, Beijing Institute of Technology, north
Capital university of communications, University Of Chongqing, China Science & Technology University and Harbin Institute of Technology etc. expand a large amount of for SOC estimation
It studies and has carried out deep exploration；Lot of domestic and international periodical, such as Journal of Power Sources, Applied
Energy, IEEE Transactions on Power Systems and power technology etc., set up the very strong column of specific aim
It is shown for related research result；Problem is estimated for the SOC of lithium ion battery, and correlative study worker obtains both at home and abroad at present
Huge progress；As described in Hu etc., primarily now there are current integration method (Ampere hour, Ah), open circuit voltage method
(Open Circuit Voltage, OCV), Kalman filtering and its expansion algorithm, particle filter method (Particle Filter,
) and neural network (Neural Network, NN) etc. PF；Due to by charging and discharging currents, temperature, internal resistance, self discharge and aging
The influence of equal factors, performance of lithium ion battery variation will generate apparent influence on SOC estimation precision, there is no general
Method is realized that SOC value obtains and is accurately estimated；In addition in groups in the course of work between monomer consistency must influence and aviation operating condition obtain it is special
Different to require, aviation Li-ion batteries piles still lack effective SOC estimation method；The SOC estimation of aerospace applications passes through base at present
This ampere-hour integration method is realized, but estimation error is larger, and is influenced by factors so that cumulative effect is obvious；
Estimate that research, above-mentioned correlative study provide thinking reference for the SOC of aviation Li-ion batteries piles；It navigates on this basis
SOC estimation method under empty operating condition is explored, and is realized and is estimated effective SOC of aviation Li-ion batteries piles；Meanwhile for aviation at
Group application needs to consider that each battery cell equilibrium state carries out SOC estimation in group, and then carries out effective energy management using BMS；
The SOC appraising model with parameters revision and regulating power is constructed, it is theoretical with the parameter estimation based on equivalent-circuit model, at
For the trend of SOC estimation development, seeks optimal balance point between improving precision and reducing calculation amount, continue to optimize and improve estimation
Method.
In existing aviation Li-ion batteries piles BMS application, based on the SOC estimation method of ampere-hour integral and open-circuit voltage, not
Accumulated error present in energy accurate characterization SOC estimation, and parameters revision cannot be carried out in conjunction with current state；By existing
SOC estimation method analysis, is based on Unscented kalman algorithm research, inputs parameter using closed circuit voltage, electric current and temperature as real-time,
The work information that aviation Li-ion batteries piles are considered in SOC estimation process, overcomes traditional SOC estimation method and corrects in real time not
The disadvantages of error caused by foot is larger and builds up；Problem is estimated for the SOC of aviation Li-ion batteries piles, in conjunction with difference
The benefit analysis of Linearization Method and iterative process, proposition simplify particle Unscented kalman algorithm and carry out iteration meter
Technique study is calculated, the building and experimental verification of SOC appraising model are realized.
Summary of the invention
The purpose of the present invention is overcoming the shortcomings of existing Li-ion batteries piles SOC estimation method, one kind is provided and is based on simplifying
The Li-ion batteries piles SOC estimation method of particle Unscented transform, solve lithium ion battery apply in groups in SOC value accurately estimate and ask
Topic.
Present invention is mainly used for Li-ion batteries piles SOC estimation is sought, handled by simplifying three particles and dual Sigmaization
Process realizes effective iterative calculation of Li-ion batteries piles SOC value；This method is calculated in the weight coefficient of sample data sequence
On the basis of, by carrying out the Unscented transform under three particles, realize the simplification processing of iterative process；This method is initially being weighed
On the basis of the setting that weight coefficient and dimension are 1, in conjunction with the calculating of each weight coefficient, realize weight coefficient vector in SOC estimation
Parameter pretreatment；This method is on the basis of process noise and observation noise corrected Calculation is analyzed, using in Unscented kalman
The first step and the 4th step dual Sigmaization treatment process, obtain the modified computing method of influence of noise；This method is abundant
Consider that lithium ion battery on working foundation, improves the iterative process based on Unscented kalman, will simplify particle in groups
Unscented transform thought is applied particularly to predict and modify link, realizes the foundation and SOC value of Li-ion batteries piles SOC appraising model
Mathematical iterations operation.
The present invention is to be managed based on Li-ion batteries piles power application demand and working characteristics experimental analysis in conjunction with modern scientist
Stronger applicability is had based on the Li-ion batteries piles SOC estimation method for simplifying particle Unscented transform by research idea；Needle
Target, the present invention, which are iterated calculating process optimization, accurately to be estimated to Li-ion batteries piles SOC value, realizes SOC estimation in groups
Mathematical description；The present invention is based on simplify the SOC estimation method of particle Unscented transform by simplifying three particles and dual Sigmaization
Calculation processes realize lithium ion battery effective iterative calculation that SOC is estimated in groups；On the basis of weight coefficient calculates,
The simplification processing of iterative process is realized by simplifying three particle Unscented transforms；It is 1 in initial weight coefficient and dimension
On the basis of setting, in conjunction with the calculating of each weight coefficient, parameter pretreatment of the weight coefficient vector in SOC estimation is realized；In mistake
Journey noise and observation noise corrected Calculation analysis on the basis of, using in Unscented kalman the first step and the 4th step it is dual
Sigmaization treatment process obtains the modified computing method of influence of noise；The present invention can be the lithium-ion electric under different application scene
The foundation of pond group SOC appraising model and SOC value calculate providing method reference, and with calculating, succinct, adaptability is good and with high accuracy
Advantage.
Detailed description of the invention
Fig. 1 is that the present invention is based on based on the sampling point transformation schematic diagram for simplifying particle Unscented transform.
Fig. 2 is Li-ion batteries piles SOC appraising model structural schematic diagram of the present invention.
Specific embodiment
Below by Li-ion batteries piles of the invention based on the SOC estimation method combination attached drawing for simplifying particle Unscented transform
It is described in further detail；The present invention is estimated when applying in groups for lithium ion battery based on the SOC for simplifying particle Unscented transform
Calculation problem proposes a kind of Li-ion batteries piles based on the SOC estimation method for simplifying particle Unscented transform, passes through intermittent aging
Degree measurement and real time calibration calculation processes realize the lithium ion battery Efficient Characterization that SOC is estimated in groups；Based on simplifying
Influence system of the SOC estimation method of particle Unscented transform on the basis of capacity is normalized and characterized, by ageing state to electricity
Number, which calculates, obtains the mathematical expression that aging action influences；Based on simplifying the SOC estimation method of particle Unscented transform in results of regular determination
On the basis of calibration, by rated capacity acquisition synchronous with cycle-index correlation and amendment, superposition cycle-index amendment is obtained
Functional relation；Coefficient and cycle-index corrected Calculation are influenced in aging based on the SOC estimation method for simplifying particle Unscented transform
On the basis of, in conjunction with the superposition calculation processing that two factors influence, obtaining ageing process influences modified calculating side to rated capacity
Method；This method is fully considering that lithium ion battery in groups on working foundation, in conjunction with the foundation that SOC is estimated, realizes to lithium-ion electric
The mathematical expression of pond group ageing process characteristic is constructed based on the SOC estimation scheme for simplifying particle Unscented transform；For better body
The existing present invention, is only illustrated by taking aviation Li-ion batteries piles as an example, but those skilled in the art should be ripe in the present embodiment
Know, estimating based on the SOC for simplifying particle Unscented transform for a variety of Li-ion batteries piles may be implemented in technical idea according to the present invention
It calculates；Li-ion batteries piles are described in detail based on the realization step for the SOC estimation method for simplifying particle Unscented transform below.
For SOC estimation precision target is improved, based on Unscented transform processing to the non-linear spy of aviation Li-ion batteries piles
Sign is described, and effectively avoids Taylor series expansion and gives up estimation error brought by high-order term；Place based on Unscented transform
Reason process at least has second order accuracy, reaches third-order particularly with Gaussian Profile compared with Taylor series expansion；No mark becomes
The selection for changing sampled point is that the correlated series based on priori mean value and priori covariance matrix square root are realized, principle such as Fig. 1
It is shown.
In Fig. 1, Unscented transform shows good performance in SOC estimation process, but if when linear process is small
The stability of section cannot continue one effective time, it will generate poor estimation effect；Pass through non-linear function transformation
Transformed Sigma data point is obtained, obtains transformed mean value and covariance using data point weighting, and then obtain its weighting
The factor；Simultaneously, it is contemplated that the reliability and real-time that embedded mode is realized are optimized processing to Unscented transform, realize essence
Simple particle Unscented transform SP-UT；By way of simplifying particle, chooses the SOC value that linear Kalman estimation obtains and be used as wherein
One particle；Reality of the particle as remaining two particles, for iterative process is respectively chosen in the symmetrical two sides of the value
It is existing；It is analyzed by the working characteristics to aviation Li-ion batteries piles, realizes that nonlinear transformation is handled using RP-UT；The change
It changes process and seeks seeking with based on spreading kalman relative to direct curve matching, have to nonlinear characteristic stronger suitable
Ying Xing, using simplify three particles seek thinking rationally and have the advantages that calculation amount is small.
In conjunction with the S-ECM state-space model of aviation Li-ion batteries piles, the iterative calculation based on Unscented kalman is realized
The iterative calculation of SOC value, for when tracking aviation Li-ion batteries piles output voltage, average estimation error to be 0.01V, maximum
Estimation error is 0.05V；By exporting change of the closed circuit voltage as observational equation using SOC as the variable in its state equation
Amount constructs state equation and observational equation expression formula；SOC(k) it is state variable, bekMomentSOCValue；U L (k) it is work electricity
Pressure output observational variable；State Equation CoefficientsAFor sytem matrix,BTo control input matrix；HFor observing matrix, initial value is
[0 0 1]；System noise parameterw(k)With observation noise parameterv(k) it is white Gaussian noise, covariance is respectivelyQWithR；U L
(k) it is to consider measurement errorv(k)The voltage signal of influence exports；By iterative calculation, from Last status valueSOC(k-1)、
Input signalI(k) and measuring signalU L (k) calculate the estimated value of Kalman modelSOC(k)；Shape is replaced using Unscented transform
State variable statistical property transformation to linearity, for different momentskValue has white Gaussian noisew(k)Random vectorSOCWith
With white Gaussian noisev(k) observational variableU L (k) constitute Discrete time Nonlinear Systems；By the estimation frame application
In estimation process, building aviation Li-ion batteries piles SOC appraising model is as shown in Figure 2.
In Fig. 2, the S1 stage indicates the calculating process of state equation, and the S2 stage indicates the calculating process of observational equation；In order to
Make its estimation process that there is better stability and higher precision, Unscented transform has been introduced into SOC estimation process, thus
It is set not need to do Jacobian matrix calculating to state equation and observational equation；This method is not necessarily to nonlinear state equation functionsf(*) and observational equation functiong(*) makees linearization process, and testing number strong point is found out using UT treatment process；Then, these
The Gaussian probability density data sequence at SOC sample number strong point is applied to non-linear state space probability function finding process；Sample
The selection of data point is to be handled based on Unscented transform, and priori mean value and mean variance is combined to realize, is used for aviation lithium-ion electric
In the state space description of pond group SOC estimation；This 2n+ 1 dimension Sigma data set and its weight coefficient pass through following formula Unscented transform
Processing obtains；Based on this process, the SOC statistical nature of aviation Li-ion batteries piles is calculated, data set is obtained by formula 1
.
(1)
In formula,nThe state dimension of characterize data collection,iCharacterize the of sample data sequence and its covariance matrixiColumn；VariancePFor
The transposition of its arithmetic square root and the subduplicate product that counts, the calculation expression that functional relation meets are as shown in Equation 2.
(2)
The Unscented kalman iterative process is realized by following steps；Firstly, by carrying out reset condition point to state value
Cloth screening, obtains aviation Li-ion batteries piles testing number strong point；Then, the destination sample data point these screened substitutes into
In state equation and observational equation；In turn, the data point of nonlinear equation is obtained, and these data points analyze to obtain
To its mean value and variance yields；By this calculating process, mean value and variance precision without linearization process reach second order, than using
The spreading kalman estimation precision that Taylor series expansion is realized is higher；And then calculate the corresponding weight of these sampled points, the weight
The weight coefficient of finding process that is, sample data sequence is sought by formula 3.
(3)
In formula, subscriptmFor mean value, the mean value of the Sigma data point set about SOC is indicated；cFor covariance, characterize about SOC value
Sigma data point set variance；SubscriptiIt isiA sampled point indicates the sequence number of sampled data points；λ is whole pantograph ratio
Example coefficient adjusts the size of its value by parameters revision to reduce the error of SOC estimation；λ=α2(n+k)-nIt is characterization pantograph ratio
The scalar parameter of example, for reducing SOC estimation error；The selection of α determines the state distribution about SOC value sequence, Jin Er
Matrix (n+λ)PUnder the premise of being positive semidefinite matrix, the value of parameter κ is obtained；By the selection of nonnegative curvature factor beta, state is incorporated
The statistical error of space equation higher order term, to ensure the influence in Unscented transform comprising higher order term.
Since the quantity of computation complexity and data point is positively correlated in SOC estimation process, using less in conversion process
Data point it is more advantageous to integra-tion application；The conversion process needs to select 2n+ 1 data point, makes in this process
WithnTo indicate the dimension of the non-linear SOC appraising model of aviation Li-ion batteries piles；By the way that the conversion process is included in aviation
In Li-ion batteries piles SOC estimation process, enablen=1, it is only necessary to 2nThe iterative process can be completed in+1=3 data points；InnIt ties up in non-linear aviation Li-ion batteries piles SOC estimation process, initial weight coefficientW 0By assignment first,W 0Selection only influence
The quadravalence of Sigma data point set or more high-order term；By rightW 0WithnAnalysis, choose remaining fromW 1It arrivesW n Weight coefficient；
Pass through weight coefficientW 1It obtainsXFirst three element vector from 0 to 2, required for producingn+ 2 havenThe number of dimensional feature
According to sequence of point sets, the vector is made to obtain recursive operation in SOC estimation process；By above-mentioned calculating process, Unscented transform is realized
Processing, and then in the parameter preprocessing process of aviation Li-ion batteries piles SOC estimation.
For different momentsk, which includes fusion white Gaussian noisew(k) stochastic regime variableSOC, with
And incorporate white Gaussian noisev(k) observation stochastic variableU L (k)；f(*) it is a nonlinear state equation, for describing aviation
The SOC state of Li-ion batteries piles；g(*) it is a non-linear observational equation, for describing the feature of output closed circuit voltage；It makes an uproar
Sound matrixw(k) variance useQIt is described, noise matrixv(k) variance useRIt is described；In the shadow of random noise
Under sound, target, different moments are accurately estimated for aviation Li-ion batteries piles SOCkEstimation pass through following steps realize.
S1: by using a series of sampled point, Sigma sequence of data points is constituted, corresponding weight coefficient passes through
Unscented transform obtains, as shown in Equation 4.
(4)
S2: computational length 2n+ 1 Sigma sequence of data points single order prediction, calculating process description are as shown in Equation 5.
(5)
S3: calculating the one-step prediction and its variance matrix of state space variable, carries out the weighted sum of Sigma sequence of data points,
SOC estimation is realized in conjunction with each calculation expression in Unscented transform treatment process；The algorithm is in state space function with most
The latter time point replaces SOC, and need to only carry out once calculating can be obtained SOC predicted value；By 3 data points of setting come real
It now predicts process, and weighting coefficient is combined to calculate average value, the calculating process formula 6 of SOC predicted value is described.
(6)
And then the predicted value of SOC state variance is obtained, calculating process is as shown in Equation 7.
(7)
S4: for the new Sigma sequence of data points of SOC estimation process, by applying Unscented transform again to one-step prediction value
Processing obtains, and calculating process is as shown in Equation 8.
(8)
S5: the Sigma sequence of data points that previous step is obtained substitutes into the observation side of aviation Li-ion batteries piles SOC appraising model
Journey, and then the observational variable matrix for obtaining prediction is as shown in Equation 9.
(9)
S6: the prediction mean value for exporting closed circuit voltage and its autocorrelation matrix and cross-correlation matrix are calculated, and is used for aviation lithium ion
The correction link of battery pack SOC estimation；The calculating of these values is weighted summation by the predicted value to Sigma sequence of data points
It obtains, calculating process is as described below.
(1) prediction mean value is as shown in Equation 10.
(10)
(2) autocorrelation matrix is as shown in Equation 11.
(11)
(3) cross-correlation matrix is as shown in Equation 12.
(12)
S7: the Kalman gain matrix for aviation Li-ion batteries piles SOC estimation is obtained by 13 calculating process of formula.
(13)
S8: for the nonlinear characteristic in aviation Li-ion batteries piles SOC estimation process, state is updated with error covariance more
New processing is realized by following two step.
(1) state is updated to calculate by formula 14 and be obtained.
(14)
(2) error covariance is updated to calculate by formula 15 and be obtained.
(15)
In aviation Li-ion batteries piles SOC estimation process, this method is based on Kalman Algorithm frame and realizes iterative process；
SOC estimation one-step prediction calculating process in, solved by using the UT after simplifying SOC estimation mean value and variance it is non-thread
Property transfer problem, using sample sequence data set approximation characterization SOC estimation process posterior probability density, without carrying out Jacobi
Matrix calculates, and the ignored problem of higher order term is not present, so that the statistical nature has high-precision advantage, significantly reduces
Nonlinearity erron in SOC estimation process；On the basis of simplifying the transformation of three particles, at the weighting twice of Sigma data point
Reason carries out data sample mean value computation；By the above iterative process, RP-UKF is handled and improved based on Unscented transform and is calculated
Method realizes the SOC appraising model building of aviation Li-ion batteries piles.
In conclusion the present invention estimates target based on the SOC for simplifying particle Unscented transform for Li-ion batteries piles, it is comprehensive
Consider estimation precision and computation complexity, propose based on the SOC estimation method for simplifying particle Unscented transform, fully consider lithium from
On sub- battery group working foundation, in conjunction with the foundation of SOC appraising model, the iteration meter estimated Li-ion batteries piles SOC is realized
It calculates, provides basis for Li-ion batteries piles SOC estimation and working condition real-time monitoring.
Above embodiments of the invention have only carried out being based on simplifying particle Unscented transform by taking aviation Li-ion batteries piles as an example
SOC estimation explanation, but it is understood that, those skilled in the art without departing from the spirit and scope of the invention can be right
It is arbitrarily changed and is changed.
Claims (5)
1. a kind of based on the SOC estimation method for simplifying particle Unscented transform, which is characterized in that propose one kind and simplify particle without mark
Transform method realizes effectively changing for Li-ion batteries piles SOC value by simplifying three particles and dual Sigmaization treatment process
In generation, calculates.
2. one kind according to claim 1 simplifies particle Unscented transform method, which is characterized in that simplify particle Unscented transform
Method simplifies three particle Unscented transforms on the basis of the weight coefficient of sample data sequence calculates, by carrying out, and realizes iteration meter
The simplification of calculation process is handled.
3. one kind according to claim 1 simplifies particle Unscented transform method, which is characterized in that simplify particle Unscented transform
Method, in conjunction with the calculating of each weight coefficient, realizes weight coefficient vector on the basis of the setting that initial weight coefficient and dimension are 1
Parameter pretreatment in SOC estimation.
4. one kind according to claim 1 simplifies particle Unscented transform method, which is characterized in that simplify particle Unscented transform
Method utilizes the first step and the 4th step in Unscented kalman on the basis of process noise and observation noise corrected Calculation is analyzed
Dual Sigmaization treatment process, obtain the modified computing method of influence of noise.
5. one kind according to claim 1 simplifies particle Unscented transform method, which is characterized in that this method is fully considering
Lithium ion battery on working foundation, improves the iterative process based on Unscented kalman, will simplify particle without mark in groups
Transformation idea is applied particularly to predict and modify link, realizes the foundation of Li-ion batteries piles SOC appraising model and the number of SOC value
Learn interative computation.
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| 周晓凤: "纯电动汽车锂电池剩余电量估计研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
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| CN110927582A (en) * | 2019-11-13 | 2020-03-27 | 上海理工大学 | Lithium battery SOC estimation method based on multiple sigma points |
| CN112800707A (en) * | 2021-01-21 | 2021-05-14 | 西南科技大学 | Unscented particle filtering method for SOC estimation of lithium ion battery pack of large unmanned aerial vehicle |
| CN112964997A (en) * | 2021-01-21 | 2021-06-15 | 西南科技大学 | Unmanned aerial vehicle lithium ion battery peak power self-adaptive estimation method |
| CN113670314A (en) * | 2021-08-20 | 2021-11-19 | 西南科技大学 | Unmanned aerial vehicle attitude estimation method based on PI self-adaptive two-stage Kalman filtering |
| CN113670314B (en) * | 2021-08-20 | 2023-05-09 | 西南科技大学 | Unmanned aerial vehicle attitude estimation method based on PI self-adaptive two-stage Kalman filtering |
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Application publication date: 20191112 |