CN108229832A - Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method - Google Patents

Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method Download PDF

Info

Publication number
CN108229832A
CN108229832A CN201810042552.7A CN201810042552A CN108229832A CN 108229832 A CN108229832 A CN 108229832A CN 201810042552 A CN201810042552 A CN 201810042552A CN 108229832 A CN108229832 A CN 108229832A
Authority
CN
China
Prior art keywords
index
pure electric
vehicle
electric bus
road operation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201810042552.7A
Other languages
Chinese (zh)
Inventor
何杰
闫雪彤
成诚
卢文慧
刘子洋
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southeast University
Original Assignee
Southeast University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Southeast University filed Critical Southeast University
Priority to CN201810042552.7A priority Critical patent/CN108229832A/en
Publication of CN108229832A publication Critical patent/CN108229832A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0639Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40Business processes related to the transportation industry

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Theoretical Computer Science (AREA)
  • Educational Administration (AREA)
  • Marketing (AREA)
  • Development Economics (AREA)
  • General Business, Economics & Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Game Theory and Decision Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses a kind of pure electric bus selection methods based on road operation test and Fuzzy Hierarchy Method, include the following steps:1st, type selecting pure electric bus is treated to different brands, carries out road operation test after experiment element is determined;2nd, dynamic data and vehicle performance parameter itself of the vehicle in road operation test are collected;3rd, quantitative assessing index system is built;4th, evaluation index analyzed, calculated, divided rank;5th, the importance of each evaluation index is weighed using analytic hierarchy process (AHP), determines the weight of pure electric bus evaluation index tested based on road operation;6th, overall merit is carried out to different automobile types with Fuzzy Evaluation Method, calculates comprehensive evaluation value;7th, the comprehensive evaluation value of different automobile types is compared, type selecting is carried out according to the height of value.This method proposes the scientific and reasonable selection method of set of system for pure electric bus, more directly and accurately different automobile types can be carried out than choosing.

Description

Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method
Technical field
The invention belongs to the evaluation type selecting technical fields of the vehicles, more particularly to a kind of to be based on road operation test and mould Paste the pure electric bus selection method of stratification.
Background technology
In recent years, with the improvement of people's living standards, environmental pollution improvement's problem causes each side to pay high attention to, traffic row The produced pollution is put to can not be ignored.To optimize air quality, ensure living environment, public transport motorized process promotes in the whole nation Like a raging fire, wherein pure electric bus becomes each city so that its riding stability is high, zero-emission and the advantages that good economy The object of city's concern.
However, electric bus there is also continual mileage is shorter etc. be not easily overcome the shortcomings that, therefore bus operation person into During row vehicle type selection, compared to traditional bus, the type selecting process of pure electric bus is increasingly complex.
Invention content
Goal of the invention:For problems of the prior art, the present invention provides one kind based on road operation test and The pure electric bus selection method of Fuzzy Hierarchy Method proposes the scientific and reasonable type selecting of set of system for pure electric bus Method.
Technical solution:The present invention adopts the following technical scheme that:
Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method, includes the following steps:
(1) type selecting pure electric bus is treated to different brands, carries out road operation test after experiment element is determined;
(2) dynamic data and vehicle performance parameter itself of the vehicle in road operation test are collected;
(3) quantitative assessing index system is built;
(4) evaluation index analyzed, calculated, divided rank;
(5) importance of each evaluation index is weighed using analytic hierarchy process (AHP), determines the pure electric vehicle tested based on road operation The weight of public transit vehicle evaluation index;
(6) overall merit is carried out to different automobile types with Fuzzy Evaluation Method, calculates comprehensive evaluation value;
(7) comprehensive evaluation value of different automobile types is compared, type selecting is carried out according to the height of value.
Dynamic data of the vehicle in road operation test includes vehicle continual mileage s, running time tTraveling, braking Device temperature T before and after car operationBefore、TAfterwards, actual measurement mileage S, actual measurement mileage power consumption Q, failure frequency nFailure, breakdown maintenance Time tDimension
Performance parameter of the vehicle itself includes vehicle acquisition cost G, surveys the maintenance cost P under mileage, battery nameplate Battery global cycle the number t, battery capacity C, cell decay amplitude δ provided with producer.
The quantitative assessing index system include 31 grade, 10 2 grades of two level quantitative assessing index system, specially:3 A 1 grade of index includes:Reliability, economy, safety;Wherein reliability index covers continual mileage s, battery global cycle number T, battery capacity C, cell decay amplitude δ;Economic index is divided into vehicle acquisition cost G, hundred kilometers of power consumption Q*, hundred kilometers of repairs Cost P*;Safety indexes include the average value T of temperature difference before and after brakeIt is average, rate of breakdown η and vehicle trouble seriousness.
The calculation formula of the vehicle acquisition cost G is:G=G1+G2+G3-G4
Wherein G1For vehicle price, G2For the expenses of taxation, G3For other fees, G4For purchase subdization;
Described hundred kilometers of power consumption Q*Calculation formula be:
Wherein Q is the power consumption that vehicle travels S kilometers;
Described hundred kilometers of maintenance cost P*Calculation formula is:
Wherein P is the maintenance cost that vehicle travels S kilometers;
The brake mean temperature difference calculation formula is:
WhereinBrake temperature before and after car operation when respectively ith is tested, n is testing time;
The vehicle trouble Incidence calculus formula is:
The vehicle trouble seriousness is S kilometers of traveling, and n occursFailureThe repair total duration of secondary failure.
The step (5) specifically includes:
(5-1) establishes hierarchy Model, and using pure electric bus type selecting as destination layer, 1 grade of index is as criterion Layer, 2 grades of indexs treat the model of type selecting pure electric bus as solution layer as indicator layer;
(5-2) to index weights weigh relatively heavy between scale and determining each evaluation index according to 1-9 scaling laws The property wanted, including:Determine set of factors U={ u1,u2,u3, u1、u2、u3Reliability factor, the economy of respectively 1 grade evaluation index Factor and safety factor;ui={ ui1,ui2..., wherein uij(j=1,2 ...) it is j-th of index for influencing i-th of factor; Judgment matrix D is obtained, with the weight W of each index in arithmetic mean method calculating matrixq
(5-3) is calculated by the combination of each factor weight of rule layer and each index relative weighting of subordinate's indicator layer, is based on The weight of each evaluation index of pure electric bus is tested in road operation.
The step (6) specifically comprises the following steps:
(6-1) formulates each index and judges collection standard, and evaluate collection is V={ v1,v2,…,vn, the element in evaluate collection is set Determine grade and scoring, obtain opinion rating standard value vector Y=(y1,y2,…,yn), wherein yiIt is element v in evaluate collectioniIt is corresponding Scoring, i=1 ..., n;
Each evaluation index of (6-2) calculating is subordinate to angle value rij, build per level-one subordinated-degree matrix;
(6-3) calculates the pure electric bus for treating type selecting per level-one according to the weight vectors and subordinated-degree matrix per level-one Fuzzy evaluation value;
(6-4) calculates the pure electric bus comprehensive evaluation value for treating type selecting.
It is described to be subordinate to angle value rijComputational methods are:
When evaluation index parameter is proportionate with opinion rating, computational methods are:
When evaluation index parameter and negatively correlated opinion rating, computational methods are:
Wherein f (x) represents the sample magnitude of index;Min (f) and max (f) are respectively the lower bound of quantitative target value and upper Boundary.
As a preferred embodiment, after obtaining judgment matrix D in step (5-2), consistency check is carried out to verify judgment matrix Reasonability, when meeting consistency check condition, perform subsequent step, otherwise, reacquire judgment matrix D;
The consistency check specifically comprises the following steps:
The maximum eigenvalue λ of (5-2-1) calculating matrix Dmax;Calculate coincident indicatorM is judgment matrix The exponent number of D;Calculate consistency rationRI is corresponding Aver-age Random Consistency Index;
(5-2-2) is if CR<ε then meets test condition, otherwise, is unsatisfactory for test condition;ε is preset consistency ration Threshold value.
Advantageous effect:Compared to computer simulation experiment and bench simulation test, road operation trial is to examine automobile Can most direct, most reliable method, have the advantages that test result it is accurate, close to formal operation situation, can intuitively examine, comment The technical performance of valency vehicle has the advantage that can not be substituted for the Truck type choice of bus operation person.Fuzzy hierarchy synthesis will Step analysis and fuzzy evaluation integrated application can compare the relative importance between quantitative target and judge each factor Membership, challenge is divided into several levels, carries out integrated system analysis layer by layer from low to high, it is more succinct real With.
Method choice road operation trial disclosed by the invention carries out vehicle type selection as test method, and number is tested in operation According to multiple indexs such as the reliabilities, economy, safety under support, considering electric bus, meeting vehicle real road fortune In the condition of the needs of battalion, carry out vehicle with fuzzy hierarchy synthesis and compare type selecting.With traditional regular public traffic vehicle type selection phase Than the road operational characteristic of pure electric vehicle public transport is combined by the present invention with fuzzy hierarchy synthesis, it is proposed that set of system science Rational selection method based on the test data of road operation, more can be carried out directly and accurately than choosing.Data of the present invention are easy , facilitate calculating, mainly using quantitative target, reliability is high, and the follow-up developments research for pure electric bus lays the foundation.
Description of the drawings
Fig. 1 is the overview flow chart of the present invention;
Fig. 2 is the quantitative assessing index system assumption diagram that the present invention is built.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with the accompanying drawings to the specific reality of the present invention Case is applied to explain.
As shown in Figure 1, the invention discloses a kind of pure electric bus based on road operation test and Fuzzy Hierarchy Method Selection method includes the following steps:
Step 1 treats type selecting pure electric bus to different brands, carries out road operation after experiment element is determined and surveys Examination;
Test vehicle is chosen common in the market 2 bus and coach enterprises E and F and (because being related to business information, is not pointed out here specific Enterprise name), every enterprise provides the 10 meter level pure electric bus 10 newly to dispatch from the factory, and the vehicle that wherein E enterprises provide is α vehicles Type, the vehicle that F enterprises provide for β vehicles, two kinds of vehicles using night charge mode, and vehicle be satisfied by JT/T1026- 2016《Pure electric vehicle city bus general technical specifications》It is required that;Experimental enviroment (is gathered around using N local lines k1 (smooth route) and k2 Stifled route) test simultaneously, ensure that same operating mode, equal temperature, the environmental condition of equal humidity test test vehicle, Test number (TN) is 50 times;Safety-type driver of the testing crew for experienced no dangerous driving record, and trained by unified Instruction.
Step 2 collects dynamic data and vehicle performance parameter itself of the vehicle in road operation test;
α vehicle continual mileages s=225km, actual measurement mileage S=25172km, actual measurement mileage power consumption Q=22931KWH, system The dynamic average front and rear temperature difference T of deviceIt is average=11 DEG C, failure frequency nFailure=0, breakdown maintenance time tDimension=0, vehicle acquisition cost G =110 ten thousand yuan, hundred kilometers of maintenance cost P*=0, battery global cycle number t=2000, battery capacity C=324kwh, battery decline Amount of decrease degree δ=14.87% can further obtain hundred kilometers of power consumption Q*=91KWH, rate of breakdown η=0, vehicle trouble seriousness For 0min.
β vehicle continual mileages s=170km, actual measurement mileage S=29101km, actual measurement mileage power consumption Q=30840KWH, system The dynamic average front and rear temperature difference T of deviceIt is average=9 DEG C, failure frequency nFailure=14, breakdown maintenance time tDimension=177min, vehicle are purchased Ten thousand yuan, hundred kilometers maintenance cost P of cost G=110*=8 yuan/100km, battery global cycle number t=2000, battery capacity C= 324kwh, cell decay amplitude δ=14.87%, can further obtain hundred kilometers of power consumption Q*=106KWH, rate of breakdown η= 0.05th, vehicle trouble seriousness is 177min.
Step 3, structure quantitative assessing index system;
The quantitative assessing index system that the present invention is built include 31 grade, 10 2 grades of two level quantitative assessing index system, Specially:31 grade of indexs include:Reliability, economy, safety;Wherein reliability index covers continual mileage s, and battery is total Cycle-index t, battery capacity C, cell decay amplitude δ;Economic index is divided into vehicle acquisition cost G, hundred kilometers of power consumption Q*, hundred Kilometer maintenance cost P*;Safety indexes include the average value T of temperature difference before and after brakeIt is average, rate of breakdown η and vehicle are former Hinder seriousness, as shown in Figure 2.
Step 4 analyzes evaluation index, is calculated, divided rank;
(1) since the pure electric bus continual mileage of different model of different manufacturers production is different from, but from universal Market situation reflection from the point of view of, continual mileage 200km between 300km pure electric bus accounting weight it is larger;
(2) the global cycle number of pure electric vehicle bus battery is referred to the national standard put into effect in 2015《Electronic vapour Power train in vehicle application battery cycle life requires and test method (GB/T 31484-2015)》To detect experiment.Wherein standard cycle Service life is defined as:When carrying out standard cycle life test, discharge capacity should be not less than initial capacity when cycle-index reaches 500 times 90% or cycle-index when reaching 1000 times discharge capacity should be not less than the 80% of initial capacity.
Since Electric Transit battery is a variety of using lead-acid battery, ferric phosphate lithium cell, lithium titanate battery etc. on the market at present Material, global cycle number are also differed from 500 to 2000.
(3) electricity of the battery of e-bus also can normally be declined with the resting period and using the increase of mileage Subtract.Public Transit Enterprises new energy public transit vehicle according to hundred Ren Hui summer forums of Electric Cars in China in 2016 uses Condition survey and special investigation are the results show that new energy public transport battery average attenuation First Year 6.05%, second year 9.77%, and 3 years 14.87% (reaching 20%, be not suitable as power battery use);
(4) remaining indices grade classification is according to market survey result and expert's opinion;
(5) according to (1) (2) (3) (4), indices according to pure electric vehicle public transport market general level be divided into " outstanding ", " compared with Well ", " general ", " poor " four grades, as shown in table 1.
The grade classification of the every evaluation index of table 1
Step 5, the importance that each evaluation index is weighed using analytic hierarchy process (AHP), determine the pure electricity tested based on road operation The weight of electric bus evaluation index;Specifically comprise the following steps:
(5-1) establishes hierarchy Model, and using pure electric bus type selecting as destination layer, 1 grade of index is as criterion Layer, 2 grades of indexs are as indicator layer, and two kinds of model pure electric bus of α and β are as solution layer;
(5-2) to index weights weigh relatively heavy between scale and determining each evaluation index according to 1-9 scaling laws The property wanted, including:Determine set of factors U={ u1,u2,u3, u1、u2、u3Reliability factor, the economy of respectively 1 grade evaluation index Factor and safety factor;ui={ ui1,ui2..., wherein uij(j=1,2 ...) it is j-th of index for influencing i-th of factor; Judgment matrix D is obtained, with the weight W of each index in arithmetic mean method calculating matrixq
(5-3) is calculated by the combination of each factor weight of rule layer and each index relative weighting of subordinate's indicator layer, is based on The weight of each evaluation index of pure electric bus is tested in road operation.
According to 1-9 scaling laws and expert's evaluation result, the weight judgment matrix of rule layer is:
The judgment matrix of 2 rule layer of table
Reliability u1 Economy u2 Safety u3 Wi
u1 1 2 1 0.4
u2 1/2 1 1/2 0.2
u3 1 2 1 0.4
Using the maximum eigenvalue λ of Matlab calculating matrix Dmax;Calculate coincident indicatorM is judges The exponent number of matrix D;Calculate consistency rationRI is corresponding Aver-age Random Consistency Index, can be obtained by tabling look-up ;Consistency ration threshold value is set as 0.1 in the present embodiment, if CR<0.1 meets test condition, otherwise, is unsatisfactory for examining Condition.It is computed, consistency check is met in the present embodiment, i.e., the weight judgment matrix is reasonable.The weight of the rule layer is Reliability index weight 0.4, economic index weight 0.2, safety indexes weight 0.4, i.e. W0={ 0.4,0.2,0.4 }.
The weight judging result of indicator layer is:Reliability covers course continuation mileage index weights 0.411, battery global cycle number Index weights 0.251, battery capacity index weights 0.087, cell decay amplitude index weight 0.251, i.e. W1=0.411, 0.251,0.087,0.251};Economy covers 0.529, hundred kilometer of indicator of power consumption weight of vehicle acquisition cost index weights 0.309th, hundred kilometers of maintenance cost index weights 0.162, i.e. W2={ 0.529,0.309,0.162 };Brake is covered in safety Mean temperature difference index weights 0.162, vehicle trouble incidence index weights 0.309, vehicle trouble severity index weight 0.529, i.e. W3={ 0.162,0.309,0.529 }.
Step 6 carries out overall merit with Fuzzy Evaluation Method to different automobile types, calculates comprehensive evaluation value;Specifically include as Lower step:
(6-1) formulates each index and judges collection standard, and evaluate collection is V={ v1,v2,…,vn, the element in evaluate collection is set Determine grade and scoring, obtain opinion rating standard value vector Y=(y1,y2,…,yn), wherein yiIt is element v in evaluate collectioniIt is corresponding Scoring, i=1 ..., n;
In the present embodiment evaluate collection be { outstanding, preferably, generally, poor }, respectively corresponding grade 1 (outstanding), grade 2 (compared with Well), grade 3 (general), class 4 (poor), (outstanding) scoring of middle grade 1 is 4 points, successively decreases successively, obtains opinion rating mark Quasi- value vector Y=(4,3,2,1);
Each evaluation index of (6-2) calculating is subordinate to angle value rij, build per level-one subordinated-degree matrix;
It is described to be subordinate to angle value rijComputational methods are:
When evaluation index parameter is proportionate with opinion rating, computational methods are:
When evaluation index parameter and negatively correlated opinion rating, computational methods are:
Wherein f (x) represents the sample magnitude of index;Min (f) and max (f) are respectively the lower bound of quantitative target value and upper Boundary.
Each index degree of membership that the present embodiment calculates is as shown in Table 3 and Table 4;
3 α vehicles degree of membership of table calculates
4 β vehicles degree of membership of table calculates
Reliability, economy and the fuzzy evaluating matrix of safety of α vehicles be respectively:
(6-3) calculates the pure electric bus for treating type selecting per level-one according to the weight vectors and subordinated-degree matrix per level-one Fuzzy evaluation value;
Level-one fuzzy overall evaluation:
The fuzzy evaluation of α vehicle vehicle reliabilities is:
The fuzzy evaluation of α vehicle vehicle economies is:
The fuzzy evaluation of α vehicle vehicle safeties is:
It can similarly obtain:
The fuzzy evaluation of β vehicle vehicle reliabilities is:
B21=W1·R21=(0.251 0.560 0.753 1)
The fuzzy evaluation of β vehicle vehicle economies is:
B22=W2·R22=(0.033 0.162 0.511 1)
The fuzzy evaluation of β vehicle vehicle safeties is:
B23=W3·R23=(0 0.205 0.471 1)
Secondary Fuzzy Comprehensive Evaluation:
By rule layer weight sets W0Evaluations matrix R with being respectively evaluated projectiBe combined calculating, obtain evaluation result to Measure Bi
α vehicle two level overall merits:B1=W0·R1=(0.468 0.684 0.908 1)
β vehicle two level overall merits:B2=W0·R2=(0.107 0.338 0.592 1)
Middle R calculated above1=(B11,B12,B13)T, R2=(B21,B22,B23)T
(6-4) calculates the pure electric bus comprehensive evaluation value for treating type selecting;
Opinion rating standard value vector Y=(4,3,2,1) in the present embodiment, comprehensive evaluation value Z's is calculated as:
Z=BYT
For 2 kinds of vehicles to be measured, Z is calculated respectivelyα=6.74, Zβ=3.63, the overall merit that can obtain α type vehicles is scored at The overall merit of 6.74, β vehicles is scored at 3.63.
Step 7 is compared the comprehensive evaluation value of different automobile types, and type selecting is carried out according to the height of value.
Each scheme is ranked up according to overall merit score, comparison result 6.74>3.63, according to vehicle opinion rating Standard, score is higher, and vehicle evaluation result is better, so the superiority-inferiority of vehicle type selection is ordered as α vehicles>β vehicles are chosen most Excellent scheme, therefore α vehicles are selected as operation vehicle.
Above-described embodiment shows that the present invention quick and convenient accurately can carry out type selecting to pure electric bus.

Claims (9)

1. the pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method, which is characterized in that including as follows Step:
(1) type selecting pure electric bus is treated to different brands, carries out road operation test after experiment element is determined;
(2) dynamic data and vehicle performance parameter itself of the vehicle in road operation test are collected;
(3) quantitative assessing index system is built;
(4) evaluation index analyzed, calculated, divided rank;
(5) importance of each evaluation index is weighed using analytic hierarchy process (AHP), determines the pure electric vehicle public transport tested based on road operation The weight of vehicle evaluation index;
(6) overall merit is carried out to different automobile types with Fuzzy Evaluation Method, calculates comprehensive evaluation value;
(7) comprehensive evaluation value of different automobile types is compared, type selecting is carried out according to the height of value.
2. the pure electric bus selection method according to claim 1 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, dynamic data of the vehicle in road operation test includes vehicle continual mileage s, running time tTraveling, system Dynamic device temperature T before and after car operationBefore、TAfterwards, actual measurement mileage S, actual measurement mileage power consumption Q, failure frequency nFailure, failure dimension Repair time tDimension
3. the pure electric bus selection method according to claim 1 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, performance parameter of the vehicle itself includes vehicle acquisition cost G, the maintenance cost P under mileage, battery inscription are surveyed Battery global cycle the number t, battery capacity C, cell decay amplitude δ that board and producer provide.
4. the pure electric bus selection method according to claim 2 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, the quantitative assessing index system include 31 grade, 10 2 grades of two level quantitative assessing index system, specifically For:31 grade of indexs include:Reliability, economy, safety;Wherein reliability index covers continual mileage s, battery global cycle Number t, battery capacity C, cell decay amplitude δ;Economic index is divided into vehicle acquisition cost G, hundred kilometers of power consumption Q*, hundred kilometers Maintenance cost P*;Safety indexes include the average value T of temperature difference before and after brakeIt is average, rate of breakdown η and vehicle trouble are tight Principal characteristic.
5. the pure electric bus selection method according to claim 4 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, the calculation formula of the vehicle acquisition cost G is:
G=G1+G2+G3-G4
Wherein G1For vehicle price, G2For the expenses of taxation, G3For other fees, G4For purchase subdization;
Described hundred kilometers of power consumption Q*Calculation formula be:
Wherein Q is the power consumption that vehicle travels S kilometers;
Described hundred kilometers of maintenance cost P*Calculation formula is:
Wherein P is the maintenance cost that vehicle travels S kilometers;
The brake mean temperature difference calculation formula is:
WhereinBrake temperature before and after car operation when respectively ith is tested, n is testing time;
The vehicle trouble Incidence calculus formula is:
The vehicle trouble seriousness is S kilometers of traveling, and n occursFailureThe repair total duration of secondary failure.
6. the pure electric bus selection method according to claim 4 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, the step (5) specifically includes:
(5-1) establishes hierarchy Model, and using pure electric bus type selecting as destination layer, 1 grade of index is as rule layer, and 2 Grade index treats the model of type selecting pure electric bus as solution layer as indicator layer;
(5-2) is carried out weighing scale and is determined the relative importance between each evaluation index according to 1-9 scaling laws to index weights, Including:Determine set of factors U={ u1,u2,u3, u1、u2、u3The reliability factor of respectively 1 grade evaluation index, economic factors and Safety factor;ui={ ui1,ui2..., wherein uij(j=1,2 ...) it is j-th of index for influencing i-th of factor;Sentenced Disconnected matrix D, with the weight W of each index in arithmetic mean method calculating matrixq
(5-3) is calculated by the combination of each factor weight of rule layer and each index relative weighting of subordinate's indicator layer, is obtained based on road The weight of operation test each evaluation index of pure electric bus.
7. the pure electric bus selection method according to claim 6 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, the step (6) specifically comprises the following steps:
(6-1) formulates each index and judges collection standard, and evaluate collection is V={ v1,v2,…,vn, the element in evaluate collection is set etc. Grade and scoring, obtain opinion rating standard value vector Y=(y1,y2,…,yn), wherein yiIt is element v in evaluate collectioniIt is corresponding to comment Point, i=1 ..., n;
Each evaluation index of (6-2) calculating is subordinate to angle value rij, build per level-one subordinated-degree matrix;
(6-3) is calculated according to the weight vectors and subordinated-degree matrix per level-one and is treated that the pure electric bus of type selecting is obscured per level-one Evaluation of estimate;
(6-4) calculates the pure electric bus comprehensive evaluation value for treating type selecting.
8. the pure electric bus selection method according to claim 1 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, described be subordinate to angle value rijComputational methods are:
When evaluation index parameter is proportionate with opinion rating, computational methods are:
When evaluation index parameter and negatively correlated opinion rating, computational methods are:
Wherein f (x) represents the sample magnitude of index;Min (f) and max (f) is respectively lower bound and the upper bound of quantitative target value.
9. the pure electric bus selection method according to claim 6 based on road operation test and Fuzzy Hierarchy Method, It is characterized in that, after obtaining judgment matrix D in step (5-2), consistency check is carried out, when meeting consistency check condition, Subsequent step is performed, otherwise, reacquires judgment matrix D;
The consistency check specifically comprises the following steps:
The maximum eigenvalue λ of (5-2-1) calculating matrix Dmax;Calculate coincident indicatorM is judgment matrix D's Exponent number;Calculate consistency rationRI is corresponding Aver-age Random Consistency Index;
(5-2-2) is if CR<ε then meets test condition, otherwise, is unsatisfactory for test condition;ε is preset consistency ration threshold Value.
CN201810042552.7A 2018-01-17 2018-01-17 Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method Pending CN108229832A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810042552.7A CN108229832A (en) 2018-01-17 2018-01-17 Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810042552.7A CN108229832A (en) 2018-01-17 2018-01-17 Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method

Publications (1)

Publication Number Publication Date
CN108229832A true CN108229832A (en) 2018-06-29

Family

ID=62640498

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810042552.7A Pending CN108229832A (en) 2018-01-17 2018-01-17 Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method

Country Status (1)

Country Link
CN (1) CN108229832A (en)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111368366A (en) * 2018-12-06 2020-07-03 比亚迪股份有限公司 Method and device for analyzing health state of vehicle part and storage medium
CN111797460A (en) * 2020-05-21 2020-10-20 武汉理工大学 Method and device for selecting type of equipment of cruise ship air conditioning system
CN112183947A (en) * 2020-09-07 2021-01-05 中车工业研究院有限公司 Rail transit vehicle comprehensive evaluation method and device, electronic equipment and storage medium
CN112396127A (en) * 2020-12-04 2021-02-23 东软睿驰汽车技术(沈阳)有限公司 Vehicle part model selection method and device and related product
CN112419705A (en) * 2020-11-06 2021-02-26 杭州图软科技有限公司 Public transit intelligent dispatching system based on big data
CN115964810A (en) * 2023-03-16 2023-04-14 中国重汽集团济南动力有限公司 Vehicle seat dynamic comfort evaluation and model selection method

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105046407A (en) * 2015-06-25 2015-11-11 国家电网公司 Risk assessment method for power grid and user bidirectional interactive service operation mode
CN106960279A (en) * 2017-03-16 2017-07-18 天津大学 Consider the electric automobile energy efficiency power plant characteristic parameter appraisal procedure of user's participation
CN107145623A (en) * 2017-03-28 2017-09-08 浙江云迪电气科技有限公司 A kind of dynamic property of pure electric automobile energy computational methods based on C# host computers
CN107464033A (en) * 2016-11-14 2017-12-12 威凯检测技术有限公司 Sweeping robot intelligent characteristic grade evaluation method based on Fuzzy Level Analytic Approach

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105046407A (en) * 2015-06-25 2015-11-11 国家电网公司 Risk assessment method for power grid and user bidirectional interactive service operation mode
CN107464033A (en) * 2016-11-14 2017-12-12 威凯检测技术有限公司 Sweeping robot intelligent characteristic grade evaluation method based on Fuzzy Level Analytic Approach
CN106960279A (en) * 2017-03-16 2017-07-18 天津大学 Consider the electric automobile energy efficiency power plant characteristic parameter appraisal procedure of user's participation
CN107145623A (en) * 2017-03-28 2017-09-08 浙江云迪电气科技有限公司 A kind of dynamic property of pure electric automobile energy computational methods based on C# host computers

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
岳惊涛 等: "车辆产品选型中的多因素多层次模糊综合评判方法", 《中国汽车工程学会2003学术年会》 *
张小辉 等: "基于AHP方法的秦皇岛市公路客运枢纽布局规划", 《山东交通科技》 *
窦宝华 等: "基于层次分析法的公交车天然气发动机选型研究", 《中国高新技术企业》 *
薄坤 等: "大城市中心区新能源公交车选型决策方法研究", 《第九届中国智能交通年会大会论文集》 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111368366A (en) * 2018-12-06 2020-07-03 比亚迪股份有限公司 Method and device for analyzing health state of vehicle part and storage medium
CN111797460A (en) * 2020-05-21 2020-10-20 武汉理工大学 Method and device for selecting type of equipment of cruise ship air conditioning system
CN112183947A (en) * 2020-09-07 2021-01-05 中车工业研究院有限公司 Rail transit vehicle comprehensive evaluation method and device, electronic equipment and storage medium
CN112183947B (en) * 2020-09-07 2024-05-14 中车工业研究院有限公司 Rail transit vehicle comprehensive evaluation method and device, electronic equipment and storage medium
CN112419705A (en) * 2020-11-06 2021-02-26 杭州图软科技有限公司 Public transit intelligent dispatching system based on big data
CN112419705B (en) * 2020-11-06 2021-10-19 杭州图软科技有限公司 Public transit intelligent dispatching system based on big data
CN112396127A (en) * 2020-12-04 2021-02-23 东软睿驰汽车技术(沈阳)有限公司 Vehicle part model selection method and device and related product
CN112396127B (en) * 2020-12-04 2024-06-11 东软睿驰汽车技术(沈阳)有限公司 Vehicle part type selection method and device and related products
CN115964810A (en) * 2023-03-16 2023-04-14 中国重汽集团济南动力有限公司 Vehicle seat dynamic comfort evaluation and model selection method

Similar Documents

Publication Publication Date Title
CN108229832A (en) Pure electric bus selection method based on road operation test and Fuzzy Hierarchy Method
Yu et al. Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving
Chatti et al. Estimating the effects of pavement condition on vehicle operating costs
CN112539816B (en) Dynamic weighing correction method based on deep neural network in digital twin environment
Song et al. Estimation of fuel efficiency of road traffic by characterization of vehicle-specific power and speed based on floating car data
CN112201038A (en) Road network risk assessment method based on risk of bad driving behavior of single vehicle
CN109243178A (en) Town way Traffic Safety Analysis and evaluation method under the conditions of a kind of bad climate
CN103091480A (en) Entropy weight-based underground road bituminous pavement service performance evaluation method
CN108985833A (en) A kind of method and system of vehicle valuation
CN103543020B (en) A kind of method based on the second-hand automobile newness rate of in good time technology for detection data evaluation
CN106548272A (en) A kind of electric automobile fills the evaluation methodology of facility combination property soon
Ren et al. Inter-city passenger transport in larger urban agglomeration area: emissions and health impacts
CN105868865A (en) Electric vehicle parc prediction method based on multivariate linear regression method and proportional substitution method
CN106651210A (en) CAN data-based driver comprehensive quality evaluation method
CN112051048B (en) Hollow slab bridge hinge joint rapid evaluation method based on action of power of moving vehicle
CN105184420A (en) Charging station planning scheme evaluation method based on grey relational analysis
CN104616496A (en) Catastrophe theory based power grid blackout traffic jam degree evaluation method
CN107273605A (en) Actual measurement axle load spectrum based on multiple classification device system determines method
Lefeng et al. External benefits calculation of sharing electric vehicles in case of Chongqing China
Tong et al. Developing electric bus driving cycles with significant road gradient changes: A case study in Hong Kong
Sun et al. A prediction-evaluation method for road network energy consumption: Fusion of vehicle energy flow principle and Two-Fluid theory
CN108320083A (en) The pure electric bus operational characteristic evaluation method that qualitative and quantitative target is combined
CN115795833A (en) Traffic flow model simulation method considering driver reaction time
CN101866549A (en) Micro indicator and evaluation method of regional transportation service level
CN107292671A (en) Used car detects the quantitative assessment method of parameter

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20180629