CN102968551A - Modeling analysis method for running characteristics of electric vehicle - Google Patents
Modeling analysis method for running characteristics of electric vehicle Download PDFInfo
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- CN102968551A CN102968551A CN2012104102556A CN201210410255A CN102968551A CN 102968551 A CN102968551 A CN 102968551A CN 2012104102556 A CN2012104102556 A CN 2012104102556A CN 201210410255 A CN201210410255 A CN 201210410255A CN 102968551 A CN102968551 A CN 102968551A
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Abstract
The invention relates to a modeling analysis method for a running characteristics of an electric vehicle. The modeling analysis method for the running characteristics of the electric vehicle comprises the following steps of: A, describing the running state of the electric vehicle; B, selecting a running state variable of the electric vehicle; C, determining the mutual relation among influence factors of the running state of the electric vehicle; D, establishing an influence factor model for the running state of the electric vehicle by adopting a structural equation arithmetic system, calculating parameters of the influence factor model for the running state of the electric vehicle, and inspecting the degree of fitting of the calculation; and E, determining a final influence factor of the running state of the electric vehicle. According to the modeling analysis method for the running characteristics of the electric vehicle, Mmodeling is performed by adopting a structural equation, and thus, the travel characteristics of the electric vehicle is effectively reflected, the mutual cause and effect relation between a travel behavior and an activity participation is revealed, and an important basis is provided to the operation and development of the electric vehicle.
Description
Technical field
The present invention relates to batteries of electric automobile and fill the electrical changing station technical field, be specifically related to a kind of electric automobile operation characteristic modeling and analysis methods.
Background technology
The behavior of electric automobile individuality and be gathered into scale after behavioral trait and rule for the research and construction of electric automobile service system and fill and change electric service network planning and design etc. and all have material impact.Behavioral trait by the research and probe electric automobile, grasp the electric automobile trip characteristics data of coincideing with it, for realizing that electric automobile variation, Extraordinary value-added service provide foundation, and the development plan that can be electric automobile and fill infrastructure such as changing electric service network and traffic municipal administration provides decision-making foundation.
Mostly the space-time corresponding relation of electric automobile operation characteristic is to disperse to have the multiple dimensioned characteristics of striding in time and space.In addition, the behavioral trait of electric automobile and electric automobile user's daily life custom, to fill the many factors such as the performance of changing electric infrastructure, municipal traffic system, electric automobile self, Economic Developing Standard of Cities relevant, and these factors all have strong uncertainty mostly.Thereby the behavioral trait analysis of electric automobile is a class multiple space and time scales, has a problem of strong uncertain feature.Adopt structural equation model SEM(Structural Equation Modeling) can solve preferably this class problem.
Mostly the space-time corresponding relation of electric automobile operation characteristic is to disperse; have the multiple dimensioned characteristics of striding in time and space; in addition; the operation characteristic of electric automobile is subjected to the impact of factors; such as the battery performance of electric automobile, electric automobile user's activity characteristic, Economic Developing Standard of Cities and supporting electrical network and fill construction of changing electric infrastructure etc.; and these factors influence each other; has very strong uncertainty; in order to grasp the general characteristic of electric automobile scale operation, need to carry out emulation and positive research to the behavioral trait of electric automobile.Electric automobile operation characteristic forecast analysis model is based on integrating electric automobile trip activity space-time probability; the magnitude of traffic flow regularity of distribution; parking demand mechanism; electrokinetic cell efficiency and life-span management; fill the correlative factors such as the social property of changing electric demand change in time and space and electric automobile user and activity characteristic; these factors are carried out the characteristic quantity coupling Simulation; the behavior of electric automobile discretize to greatest extent serialization characterize; colony and individual space-time characteristic relation under the electric automobile scale service condition are proposed; electric automobile continual mileage and energetic efficiency characteristic; fill the mathematical description that changes the characteristics such as electric demand, for the electric automobile intelligent driving is assisted; state on_line monitoring; expert decision systems etc. provide data and method to support.
Summary of the invention
For the deficiencies in the prior art, the invention provides a kind of electric automobile operation characteristic modeling and analysis methods, the method adopts the equation of structure to carry out the trip characteristic that electric automobile is effectively reacted in modeling, mutual cause-effect relationship between announcement travel behaviour and the movable participation is for electric automobile operation development provides important foundation.
The objective of the invention is to adopt following technical proposals to realize:
A kind of electric automobile operation characteristic modeling and analysis methods, described method comprises the steps:
The running status of A, description electric automobile;
B, choose electric automobile running status variable;
C, determine the mutual relationship between the electric automobile running status influence factor;
D, employing equation of structure arithmetic system are set up electric automobile running status model of influencing factors, and electric automobile running status model of influencing factors parameter is calculated, and investigate the degree of fitting that calculates;
E, determine the final influence factor of electric automobile running status.
Wherein, in the described steps A, by the running status assessment electric automobile user characteristic of described electric automobile; Described electric automobile user characteristic comprises electric automobile user's social property, electric automobile user's activity characteristic, the performance of electric automobile self and the environment attribute of electric automobile operation.
Wherein, among the described step B, described electric automobile running status variable comprises built-in variable and external variable; Described external variable refers to the environment attribute of electric automobile user's social property, electric automobile self attributes and electric automobile operation; Described built-in variable refers to electric automobile user's activity characteristic and the operation characteristic of electric automobile.
Wherein, described electric automobile user's social property refers to the set of personal characteristics and family's feature; Described personal characteristics comprises age characteristics, sex character and occupational identity feature; Described family feature comprises number in the household feature, vehicles owning amount feature and family income feature.
Wherein, described sex character comprises male sex's sample and women's sample; The male sex uses electric automobile trip intensity to use electric automobile trip intensity greater than the women.
Wherein, described occupational identity is full-time employment person and full-time without the worker; Full-time employment person comprises workman, waiter, civil servant, office worker and self-employed labourer; Full-timely comprise colony unemployed, retired and that other are professional without the worker.
Wherein, described electric automobile self attributes comprises:
A, maximum course continuation mileage: electric automobile is full of electricity once to the max mileage of using up all electric weight of battery and travelling;
B, F-Zero: the speed per hour of maximum after electric automobile accelerates;
C, trouble shooting maintenance: electric automobile is used for time, the number of times of periodic maintenance, and annual average time and the time that is used for breakdown maintenance.
Wherein, the environment attribute of described electric automobile operation comprises:
I, fill and change electric infrastructure: the distribution situation of electrically-charging equipment in electric automobile user zone of action, comprise electrically-charging equipment the place the place and for the quantity of the equipment of charging;
Ii, urban traffic blocking situation: the road conditions of highway section within the time period in the electric automobile user zone of action; The degree of blocking up in highway section is represented the coefficient=average occupancy of blocking up/draw speed with the coefficient that blocks up;
Iii, policy support condition: government is for the support degree of the use of electric automobile, comprise electric automobile energy-conservation subsidy, fill the construction of changing electric infrastructure, publicity situation that electric automobile uses, provide questionnaire and estimate the policy dynamics in city to the user who uses electric automobile.
Wherein, described electric automobile user's activity characteristic comprises:
1) use electric automobile survival activity on and off duty: all be designated as activity on and off duty with work existence trip as purpose trip number of times every day;
2) activity of using electric automobile to lie fallow: movable as the resident that trip was produced of purpose with irrelevant work leisure trip, comprise life shopping, style entertainment, visit friends and relatives, see a doctor;
3) at home movable: do not go on a journey and the resident's activity that trip was produced take return as purpose be classified as movable at home.
Wherein, the operation characteristic of described electric automobile comprises:
The travel behaviour feature of I, electric automobile: the trip number of times of electric automobile is gone on a journey number of times as the reference index with individual one day electric automobile;
Consumption during II, electric automobile day trip: consumption is cumulative when using the electric automobile trip in one day, take minute as unit;
III, electric automobile day trip mileage: total electric automobile the cumulative of mileage of going on a journey altogether in a day, take kilometer as unit;
Fill IV, electric automobile day and change electric number of times: electric automobile uses the number of times that charges in the middle of a day or changes battery, is the interior average of observation sample;
V, Trip chain quantity: the Trip chain number index that selects passerby is described, and is dynamic variable; Described Trip chain number refers to that traveler finishes complete Trip chain every day, namely returns the process of home to from family's trip again;
The trip share rate of VI, car: try to achieve divided by the resident trip total degree by using the electric automobile total degree in the resident one day, represent with number percent;
VII, electric automobile travel time distribute: the time point that characterizes the electric automobile trip distributes, and is dynamic variable.
Wherein, among the described step C, determine the mutual relationship between the electric automobile running status influence factor, namely take the movable variable that participates in of resident as electric automobile user social property, electric automobile self performance and the electric automobile running environment attribute function as parameter, contacting between simulation and the resident's activity, and in conjunction with the equilibrium relation between movable duration of resident and outdoor activity duration.
Wherein, the general equation model of described method is the path relation between exogenous variable and the endogenous variable, 1. represents with following expression formula:
The y-built-in variable, p built-in variable is expressed as the vectorial array of p * l;
X-is endogenous variable, the vector representation that is comprised of the external source index;
B-is the relation between endogenous variable, is represented by relational matrix at random;
Г-be that exogenous variable is on the impact of endogenous variable, by direct stochastic effects matrix representation;
ζ-be the residual error item of the equation of structure, reflection y not construable part in equation.
Wherein, among the described step D, the parameter of described structural equation model is to realize by the structure based on covariance; The calculation of parameter of structural equation model asks the difference between sample covariance matrix and the model covariance matrix minimum; Definition Φ is the covariance matrix of described x; Definition Ψ is the covariance matrix of ζ, defines following expression formula 2.:
∑=∑(θ) ②；
Wherein: ∑ represents the population covariance matrix of observational variable; Tried to achieve by described B parameter, Г, Φ and Ψ; Employing minimizes square law evaluate parameter θ.
Wherein, among the described step D, utilize the variable data input arithmetic system that it is good that arithmetic system will be sampled, select least square method that model is found the solution, finally obtain the impact relation from the result of calculation table, described impact relation comprises direct impact, remote effect and total impact.
Wherein, in the described step e, adopt the simulating degree of the as a result display model computing of simplation examination method, the observation degree of fitting is also adjusted degree of fitting, and variance and root mean square, finally checks critical value, if critical value surpasses 200, assert that model-fitting degree is optimum; Determine the final influence factor relation of electric automobile running status.
Wherein, the final influence factor of electric automobile running status comprises electric automobile user's the social property of external variable and use electric automobile survival activity time and the at home movable duration on and off duty of built-in variable; Then the final influence factor pass of electric automobile running status is the influence factor relation between electric automobile activity characteristic and electric automobile user social property and the electric automobile operation characteristic.
Wherein, described electric automobile user's social property comprises sex character, age characteristics, job characteristics, family income feature and vehicles owning amount feature.
Compared with the prior art, the beneficial effect that reaches of the present invention is:
1 the present invention has carried out comprehensive investigation to the links that affects the electric automobile operation characteristic, electric automobile user's mechanism of action and decision path have been grasped, electric automobile self attributes and running environment have been analyzed to the concrete impact relation of electric automobile user trip, drawn the user's of different identity all ages and classes trip rule, provide reference frame to layout and the quantity of electric automobile battery charger in the city, also electric automobile has been changed power mode simultaneously the research foundation is provided;
2. the present invention has studied the many-sided influence factor of electric automobile, has chosen a large amount of variablees, and the degree of fitting that model is calculated has carried out fine control, and the data precision that provides is higher;
3. can provide the concrete result that affects to the result of calculation analysis, for the electric automobile large-scale development provides foundation.
Description of drawings
Fig. 1 is that electric automobile running status provided by the invention is described synoptic diagram;
Fig. 2 is the synoptic diagram of electric vehicle structure equation model A provided by the invention;
Fig. 3 is the synoptic diagram of electric vehicle structure equation model B provided by the invention.
Embodiment
Below in conjunction with accompanying drawing the specific embodiment of the present invention is described in further detail.
In the electric automobile operation characteristic modeling and analysis methods provided by the invention, the factor that affects the electric automobile operation mainly comprises electric automobile user's social property, electric automobile user's activity characteristic, the performance of electric automobile self and the environment attribute of electric automobile operation.Adopt the equation of structure to carry out the trip characteristic that electric automobile is effectively reacted in modeling, the mutual cause-effect relationship between announcement travel behaviour and the movable participation is for electric automobile operation development provides important foundation.
Electric automobile operation characteristic modeling and analysis methods provided by the invention comprises the steps:
The running status of A, description electric automobile:
Electric automobile running status provided by the invention is described as shown in Figure 1, how electric automobile running status announcement electric automobile user's social property, electric automobile self performance and electric automobile running environment affects the use of electric automobile, what kind of contact the electric automobile owner is possessing at home and between going out, at last by the check on the direct impact in the model system, remote effect and total impact, may recognize which information, for assessment of electric automobile user characteristic.
B, choose electric automobile running status variable, namely choose the influence factor of electric automobile running status:
Electric automobile running status variable comprises external variable and built-in variable; External variable refers to the running environment of electric automobile user's social property, electric automobile self attributes and electric automobile; Built-in variable refers to electric automobile user's activity characteristic and the operation characteristic of electric automobile.
(1) electric automobile user's social property:
Electric automobile user's social property is the set of a series of personal characteristics and family's feature.Personal characteristics comprises age characteristics, sex character and occupational identity feature; Family's feature comprises number in the household feature, vehicles owning amount feature and family income feature etc.The below specifically describes each feature:
Age characteristics: the time data sample that is used for research is that the investigation sample age level is the adult in the 18-60 year sample of going on a journey, and the ratio of age composition becomes normal distribution, and 38 years old mean age, standard deviation is 9.5 years old.
Sex character: the sex character effective sample should comprise male sex's sample, women's sample, M-F are that the male sex is higher than the women on electric automobile trip number of times, corresponding share rate and the time difference is also arranged on the consumption, the male sex uses electric automobile trip intensity to be higher than the women far away.
The occupational identity feature: investigation here is full-time employment person: comprise workman, waiter, civil servant, office worker, self-employed labourer, and full-time without the worker: unemployed, retired and other professional colonies.
The number in the household feature: having electric automobile family average population is 3.36 people, three-person household;
Vehicles owning amount feature: have the quantity of automobile and the quantity of electric automobile as the unit take family;
The annual family income feature: have the annual family income summation of electric automobile, surpass 50,000 yuan as objects of statistics.
(2) the electric automobile self attributes comprises:
A, maximum course continuation mileage: electric automobile is full of electricity once to the max mileage of using up all electric weight of battery and travelling;
B, F-Zero: the speed per hour of maximum after electric automobile accelerates;
C, trouble shooting maintenance: electric automobile is used for time, the number of times of periodic maintenance, and the average time and the time that are used for breakdown maintenance in 1 year.
(3) environment attribute of electric automobile operation:
I, fill and change electric infrastructure: the distribution situation of electrically-charging equipment in electric automobile user zone of action, comprise electrically-charging equipment the place the place and can be for the quantity of the equipment of charging;
Ii, urban traffic blocking situation: the traffic congestion situation mainly comes from the Monitoring Data of Municipal administrative authority, mainly be in the electric automobile user zone of action the highway section at a time the section in road conditions.The unimpeded of highway section is designated as 100%, the degree of blocking up in highway section is proportionally converted;
Iii, policy support condition: government is for the support degree of the use of electric automobile, and for example the construction of changing electric related facility is filled in the energy-conservation subsidy of electric automobile, and the publicity situation of the use of electric automobile is provided questionnaire, the policy dynamics in a certain city of comprehensive evaluation.
(4) electric automobile user's activity characteristic comprises:
1) use electric automobile survival activity on and off duty: all be designated as activity on and off duty with work existence trip as purpose trip number of times every day;
2) activity of using electric automobile to lie fallow: movable as the resident that trip was produced of purpose with irrelevant work leisure trip, comprise life shopping, style entertainment, visit friends and relatives, see a doctor;
3) at home movable: do not go on a journey and the resident's activity that trip was produced take return as purpose be classified as movable at home.
(5) operation characteristic of electric automobile: the individual behavior feature of resident's electric automobile is the operating characteristic of electric automobile, can use the trip number of times of electric automobile, the variablees such as trip share rate of the travel time of electric automobile, the Trip chain of electric automobile and electric automobile are described.
The travel behaviour feature of I, electric automobile: the trip number of times of electric automobile is gone on a journey number of times as the reference index with individual one day electric automobile;
Consumption during II, electric automobile day trip: consumption is cumulative when using the electric automobile trip in one day, take minute as unit; Consumption can quantize accurately during the electric automobile trip, is an important component part of electric automobile operating characteristic.
III, electric automobile day trip mileage: total electric automobile the cumulative of mileage of going on a journey altogether in a day, take kilometer as unit; Electric automobile trip mileage can quantize accurately.
Fill IV, electric automobile day and change electric number of times: electric automobile uses the number of times that charges in the middle of a day or changes battery, is the interior average of one-period;
V, Trip chain quantity: the number index that selects passerby's Trip chain is described, and is dynamic variable; Wherein the Trip chain number is that traveler is finished several complete Trip chain every day, and several processes of returning again to home from family's trip are namely arranged.
The trip share rate of VI, car: in case the resident has had electric automobile, all trips all can be selected the trip mode of electric automobile, consider ample time or economy, they also can select other modes such as modes such as walkings sometimes, and the automobile access times also may be zero among the electric automobile owner one day.For individual, the electric automobile share rate uses the electric automobile total degree to try to achieve divided by the resident trip total degree with the resident in one day, represents that with number percent can think, this is the index of research electric automobile use most critical.
Usually adopt the form of survey, please call the electrical automobile car owner and fill in.Need a large amount of sampled datas.The final general characteristic questionnaire that forms the electric automobile resident.
VII, electric automobile travel time distribute: the time point that characterizes the electric automobile trip distributes, and is dynamic variable.
C, determine the mutual relationship between the electric automobile running status influence factor:
Complicated for the Relationship Comparison of model inside, therefore the mutual relationship that goes out between the variable hard to explain needs by original model framework, set up the more effective mutual relationship that explains between the variable of the smaller model of some scales.
The key that nowadays the electric automobile user is defined as family activity gradually to the selection of all kinds of activities of house activity or outdoor activity and these movable time, the relation that has a kind of inherence is also supposed in movable and outdoor activity all the time at home.The synoptic diagram of model A as shown in Figure 2, the fundamental purpose of model A is exactly to inquire into the balance that may exist of the house that shows in resident's daily routines and outdoor activity.Movable participation variable is that electric automobile user social property, electric automobile self performance and electric automobile running environment attribute are as the function of parameter, contacting between simulation and the resident's activity, and consider at home activity duration and outdoor activity duration between equilibrium relation.
Final electric automobile operation characteristic determines that by many factors is common Fig. 3 has described the impact relation between each variable.
D, employing equation of structure arithmetic system are set up electric automobile running status model of influencing factors, and electric automobile running status model of influencing factors parameter is calculated, and investigate the degree of fitting that calculates;
Structural equation model supposes between one group of hidden variable and has cause-effect relationship that hidden variable can represent with one group of aobvious variable respectively, be the linear combination in certain several aobvious variable.By verifying the covariance between the aobvious variable, can estimate the coefficient of linear regression model (LRM), thereby whether the model of supposing in the statistics check is suitable to the process of studying, if confirm that the model of supposing is suitable, just can say that the relation between the hypothesis hidden variable is rational.
One) general equation model:
Only consider the path relation between exogenous variable and the endogenous variable, do not introduce latent variable, so structural equation model can be expressed as:
The y-built-in variable, p built-in variable is expressed as the vectorial array of p * 1;
X-is endogenous variable, the vector representation that is comprised of the external source index;
B-is the relation between endogenous variable, is represented by relational matrix at random;
Г-be that exogenous variable is on the impact of endogenous variable, by direct stochastic effects matrix representation;
ζ-be the residual error item of the equation of structure, reflection y not construable part in equation.
The parameter estimation of structural equation model is to finish by the structure based on covariance, thereby is also referred to as moment method, and the thinking of finding the solution of this method is the difference minimum of making every effort between sample covariance matrix and the model covariance matrix.Definition Φ is the covariance matrix of described x; Definition Ψ is the covariance matrix of ζ, and the basis that the equation of structure is found the solution is based on the hypothesis that covariance is estimated.The covariance matrix that is to say observation variable is some parametric equations of mentioning in the formula.
∑=∑(θ) ②；
Wherein: ∑ represents the population covariance matrix of observational variable; Tried to achieve by B parameter, Г, Φ and Ψ; Employing minimizes square law evaluate parameter θ, namely each composition of population covariance can both be write as one or more model parameter equation, or be expressed as ∑=∑ (θ), there is difference between sample equation covariance matrix S and the population covariance matrix (by unknown parameter ∑ (θ) expression), therefore come evaluate parameter θ with minimizing this parameter, since can't give in the formula all for assessment of parametric variable find out same evaluation criterion, therefore need to be to some constrained of model, so that can and deal with problems with unique standard by enough information, model consistance namely.
Two) selection of input variable:
Model is simplified, is further screened input variable, choose the apparent in view external variable of impact effect and describe the electric automobile operation characteristic key variables carry out the foundation of model.As shown in table 1 below:
Table 1 external variable and describe the electric automobile operation characteristic key variables between relation
Three) model is estimated:
The variable of definition and the variable of defined each sample of mode input are simulated by arithmetic system.Adopt the simulating degree of the as a result display model computing of different simplation examination methods, the observation degree of fitting is adjusted degree of fitting, and variance root mean square, finally checks critical value, if critical value surpasses 200, just assert that model-fitting degree is fine.
E, determine the final influence factor of electric automobile running status:
Utilize the variable data input arithmetic system that it is good that existing arithmetic system will be sampled, select least square method that model is found the solution, finally obtaining 3 classes clearly affects relation, is respectively direct impact, remote effect and total impact.Directly impact, remote effect and total impact can draw from the coefficient of result of calculation table.Directly impact, remote effect and always affect as shown in table 2 below:
Directly impact of table 2, remote effect and total impact signal table
Finally provide the estimated result of model A, illustrate that electric automobile user social property and electric automobile self attributes and environment attribute concern the balance influence between each activity, provide Model B on the basis of model A, select observational variable to have 9, wherein external variable is user's social property, it is respectively sex character, age characteristics, job characteristics, family income feature and the electric motor car quantity that has, active characteristics parameter in the built-in variable comprises the survival activity life span of going out, at home movable duration 2 parts, simplified a variation of the line duration of lying fallow out, model need to be explained the characteristics of variables of electric automobile travel behaviour: time consumption and the share rate of electric automobile trip.Because the trip number of times of electric automobile can be obtained by the achievement of the trip share rate of resident trip total degree and electric automobile.Electric automobile user social property and electric automobile self attributes and environment attribute are as shown in table 3 below to the relation of the balance influence between each activity:
Table 3 electric automobile user's social property and electric automobile self attributes and environment attribute are to the balance influence relation table between each activity
Electric automobile operation characteristic modeling and analysis methods provided by the invention adopts the equation of structure to carry out modeling and obtains the relation table that affects between electric automobile user's activity and electric automobile user social property, electric automobile running environment and the electric automobile self attributes.Finally obtained the influence factor relation between electric automobile activity characteristic and electric automobile user social property and the electric automobile operation characteristic, can effectively react the trip characteristic of electric automobile, mutual cause-effect relationship between announcement travel behaviour and the movable participation is for electric automobile operation development provides important foundation.
Should be noted that at last: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit, although with reference to above-described embodiment the present invention is had been described in detail, those of ordinary skill in the field are to be understood that: still can make amendment or be equal to replacement the specific embodiment of the present invention, and do not break away from any modification of spirit and scope of the invention or be equal to replacement, it all should be encompassed in the middle of the claim scope of the present invention.
Claims (17)
1. an electric automobile operation characteristic modeling and analysis methods is characterized in that described method comprises the steps:
The running status of A, description electric automobile;
B, choose electric automobile running status variable;
C, determine the mutual relationship between the electric automobile running status influence factor;
D, employing equation of structure arithmetic system are set up electric automobile running status model of influencing factors, and electric automobile running status model of influencing factors parameter is calculated, and investigate the degree of fitting that calculates;
E, determine the final influence factor of electric automobile running status.
2. electric automobile operation characteristic modeling and analysis methods as claimed in claim 1 is characterized in that, in the described steps A, by the running status assessment electric automobile user characteristic of described electric automobile; Described electric automobile user characteristic comprises electric automobile user's social property, electric automobile user's activity characteristic, the performance of electric automobile self and the environment attribute of electric automobile operation.
3. electric automobile operation characteristic modeling and analysis methods as claimed in claim 1 is characterized in that, among the described step B, described electric automobile running status variable comprises built-in variable and external variable; Described external variable refers to the environment attribute of electric automobile user's social property, electric automobile self attributes and electric automobile operation; Described built-in variable refers to electric automobile user's activity characteristic and the operation characteristic of electric automobile.
4. electric automobile operation characteristic modeling and analysis methods as claimed in claim 3 is characterized in that described electric automobile user's social property refers to the set of personal characteristics and family's feature; Described personal characteristics comprises age characteristics, sex character and occupational identity feature; Described family feature comprises number in the household feature, vehicles owning amount feature and family income feature.
5. electric automobile operation characteristic modeling and analysis methods as claimed in claim 4 is characterized in that, described sex character comprises male sex's sample and women's sample; The male sex uses electric automobile trip intensity to use electric automobile trip intensity greater than the women.
6. electric automobile operation characteristic modeling and analysis methods as claimed in claim 4 is characterized in that, described occupational identity is full-time employment person and full-time without the worker; Full-time employment person comprises workman, waiter, civil servant, office worker and self-employed labourer; Full-timely comprise colony unemployed, retired and that other are professional without the worker.
7. electric automobile operation characteristic modeling and analysis methods as claimed in claim 3 is characterized in that, described electric automobile self attributes comprises:
A, maximum course continuation mileage: electric automobile is full of electricity once to the max mileage of using up all electric weight of battery and travelling;
B, F-Zero: the speed per hour of maximum after electric automobile accelerates;
C, trouble shooting maintenance: electric automobile is used for time, the number of times of periodic maintenance, and annual average time and the time that is used for breakdown maintenance.
8. electric automobile operation characteristic modeling and analysis methods as claimed in claim 3 is characterized in that, the environment attribute of described electric automobile operation comprises:
I, fill and change electric infrastructure: the distribution situation of electrically-charging equipment in electric automobile user zone of action, comprise electrically-charging equipment the place the place and for the quantity of the equipment of charging;
Ii, urban traffic blocking situation: the road conditions of highway section within the time period in the electric automobile user zone of action; The degree of blocking up in highway section is represented the coefficient=average occupancy of blocking up/draw speed with the coefficient that blocks up;
Iii, policy support condition: government is for the support degree of the use of electric automobile, comprise electric automobile energy-conservation subsidy, fill the construction of changing electric infrastructure, publicity situation that electric automobile uses, provide questionnaire and estimate the policy dynamics in city to the user who uses electric automobile.
9. electric automobile operation characteristic modeling and analysis methods as claimed in claim 3 is characterized in that described electric automobile user's activity characteristic comprises:
1) use electric automobile survival activity on and off duty: all be designated as activity on and off duty with work existence trip as purpose trip number of times every day;
2) activity of using electric automobile to lie fallow: movable as the resident that trip was produced of purpose with irrelevant work leisure trip, comprise life shopping, style entertainment, visit friends and relatives, see a doctor;
3) at home movable: do not go on a journey and the resident's activity that trip was produced take return as purpose be classified as movable at home.
10. electric automobile operation characteristic modeling and analysis methods as claimed in claim 3 is characterized in that the operation characteristic of described electric automobile comprises:
The travel behaviour feature of I, electric automobile: the trip number of times of electric automobile is gone on a journey number of times as the reference index with individual one day electric automobile;
Consumption during II, electric automobile day trip: consumption is cumulative when using the electric automobile trip in one day, take minute as unit;
III, electric automobile day trip mileage: total electric automobile the cumulative of mileage of going on a journey altogether in a day, take kilometer as unit;
Fill IV, electric automobile day and change electric number of times: electric automobile uses the number of times that charges in the middle of a day or changes battery, is the interior average of observation sample;
V, Trip chain quantity: the Trip chain number index that selects passerby is described, and is dynamic variable; Described Trip chain number refers to that traveler finishes complete Trip chain every day, namely returns the process of home to from family's trip again;
The trip share rate of VI, car: try to achieve divided by the resident trip total degree by using the electric automobile total degree in the resident one day, represent with number percent;
VII, electric automobile travel time distribute: the time point that characterizes the electric automobile trip distributes, and is dynamic variable.
11. electric automobile operation characteristic modeling and analysis methods as claimed in claim 1, it is characterized in that, among the described step C, determine the mutual relationship between the electric automobile running status influence factor, namely take the movable variable that participates in of resident as electric automobile user social property, electric automobile self performance and the electric automobile running environment attribute function as parameter, contacting between simulation and the resident's activity, and in conjunction with the equilibrium relation between movable duration of resident and outdoor activity duration.
12. electric automobile operation characteristic modeling and analysis methods as claimed in claim 1 is characterized in that, the general equation model of described method is the path relation between exogenous variable and the endogenous variable, 1. represents with following expression formula:
The y-built-in variable, p built-in variable is expressed as the vectorial array of p * l;
X-is endogenous variable, the vector representation that is comprised of the external source index;
B-is the relation between endogenous variable, is represented by relational matrix at random;
Г-be that exogenous variable is on the impact of endogenous variable, by direct stochastic effects matrix representation;
ζ-be the residual error item of the equation of structure, reflection y not construable part in equation.
13. electric automobile operation characteristic modeling and analysis methods as claimed in claim 1 is characterized in that, among the described step D, the parameter of described structural equation model is to realize by the structure based on covariance; The calculation of parameter of structural equation model asks the difference between sample covariance matrix and the model covariance matrix minimum; Definition Φ is the covariance matrix of described x; Definition Ψ is the covariance matrix of ζ, defines following expression formula 2.:
∑=∑(θ) ②；
Wherein: ∑ represents the population covariance matrix of observational variable; Tried to achieve by described B parameter, Г, Φ and Ψ; Employing minimizes square law evaluate parameter θ.
14. electric automobile operation characteristic modeling and analysis methods as claimed in claim 13, it is characterized in that, among the described step D, utilize the variable data input arithmetic system that it is good that arithmetic system will be sampled, select least square method that model is found the solution, finally obtain the impact relation from the result of calculation table, described impact relation comprises direct impact, remote effect and total impact.
15. electric automobile operation characteristic modeling and analysis methods as claimed in claim 1, it is characterized in that, in the described step e, adopt the simulating degree of the as a result display model computing of simplation examination method, the observation degree of fitting is also adjusted degree of fitting, and variance and root mean square, finally checks critical value, if critical value surpasses 200, assert that model-fitting degree is optimum; Determine the final influence factor relation of electric automobile running status.
16. electric automobile operation characteristic modeling and analysis methods as claimed in claim 15, it is characterized in that the final influence factor of electric automobile running status comprises electric automobile user's the social property of external variable and use electric automobile survival activity time and the at home movable duration on and off duty of built-in variable; Then the final influence factor pass of electric automobile running status is the influence factor relation between electric automobile activity characteristic and electric automobile user social property and the electric automobile operation characteristic.
17. electric automobile operation characteristic modeling and analysis methods as claimed in claim 16 is characterized in that, described electric automobile user's social property comprises sex character, age characteristics, job characteristics, family income feature and vehicles owning amount feature.
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