CC BY
27
DOI 10.17816/transsyst201843s136-56
© A. Lascher1, M. Witt2, E. Frishman3, M. Umanov4
1 Technical University of Dresden (Dresden, Germany)
2 MW System Consult (Markdorf, Germany)
3 Department Electronics, Jerusalem College of Technology (Jerusalem, Israel)
4 Institute of the Transport Systems and Technologies of the National Academy of Sciences of Ukraine „Transmag"
(Dnepropetrovsk, Ukraine)
In this paper, the analysis of the technology of complex optimization of transport is performed on the example of various Maglev systems for the passenger and goods transport.
Keywords: Maglev technology, Maglev system, function model, optimization, system analysis.
Maglev systems are in general regarding as more expensive and having a lower profitability in relation to its investment costs as wheel-rail systems or conventional bulk systems what substantially restricts the use of Maglev systems in the planning of transport infrastructure.
Therefore, in this paper the usefulness of the technology of complex optimization of transport [1] is shown how to reduce costs of Maglev systems. Using the results this can improve their chances in competition with traditional modes of transport on the existing transport market
In accordance with the technology of complex optimization of transport, an abstract model for a generalized transport system was developed. This model determines mathematically the maximum balance between overall system components and provides adaptation of any guidedtransport system to its operation
RESULTS OF THE COMPLEX OPTIMIZATION
OF MAGLEV
1. INTRODUCTION
2. METHODS OF SOLUTION
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conditions. As a result, unnecessary costs are cut off to increase the efficiency of Maglev systems.
Two variants - internal and combined - for the optimization control of Maglev systems were implemented. For internal one, the optimal values of design parameters of Maglev systems are established automatically. For the combined one, the maximum train speed between the stops and the number of its sections are selected in a manual way while the values of other design parameters of the system are established automatically.
Also, for determination of the scopes of application of Maglev systems, a dynamic model for the development of scopes for the effective application of transport systems was developed to find the most effective transport system for every application case.
In this case the main evaluation criterion for determination of effective application of Maglev systems, as compared with the traditional types of transport, is the value of the specific travel tariff (Figure 1), which was received from the calculation of the payback of the total costs to the time of credit payment.
Fig. 1. Principles of the complex optimization process
3. INPUT DATA
The calculations were performed for four Maglevsystems:, TRANSMAG and TRANSPROGRESS as well as TRANSRAPID and MLX01.
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TRANSMAG is a Ukrainian Maglev system with aero-electrodynamic suspension, superconducting magnets and a long stator linear synchronous motor (Figure 2). It was developed at the Institute of Transport Systems and Technologies
шшзШ
шштт^
(c) test line of aerodynamic suspension of the vehicle (Dnepropetrovsk city, Ukraine)
(a) Aerodynamic suspension
(d) Superconducting magnet
Specifications:
max. speed: 800 km/h;
section:
weight: 36 t, length: 40 m, height: 3 m, wingspan: 6 m, width: 4 m; passenger capacity: 120 person.
(b) Track-train structure
(e) Test track of aero-electrodynamic suspension of the vehicle (Dnepropetrovsk city, Ukraine)
Fig. 2. TRANSMAG Maglev system test vehicle and test trackline
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of National Academy of Sciences of Ukraine [2]. The economic component of the calculations of TRANSMAG was obtained in accordance with the internal market prices.
TRANSPROGRESS is the Russian Maglev system on permanent magnetic suspension of vertical type with a short stator linear asynchronous motor (developed in the design office "Transprogress" (Moscow) from 1986 to 1990), intended for transportation of friable goods in ore mining and metallurgical enterprises Fig. 3 [3].
1 - magnets of the vehicle
2 - magnets of the track structure
3 - stabilization rollers
4 - bodywork of the vehicle
5 - track structure
Specifications:
- length of test line: 250 m;
- speed: 11 km/h;
- weight of train: 6 t;
- specific payload: 500 kg per linear m;
- train resistance is 20 times < than at a railway system;
- specific energy consumption is 5 times < than at a railway system.
Fig. 3. TRANSPROGRESS Maglevsystem on test track
On the basis of an abstract model for a generalized transport system for each of these Maglev systems an algorithm was written. For TRANSRAPID and MLX01, the principle of combined optimization control was applied, and for TRANSMAG and TRANSPROGRESS the internal one was used.
Calculations of TRANSRAPID and MLX01 performed for the selected model lines and for lines in operation as described in Table 1.
For TRANSMAG and TRANSPROGRESS, calculations were carried out for an array of input data that characterize a set of model lines. For TRANSMAG, the length of line was taken in the range from 250 to 4 500 km, and traffic volumes varied from 1 to 25 million passengers per year. For TRANSPROGRESS, the line
(b) Structure of a vertical magnetic suspension
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Table 1. Initial design data of various lines TRANSRAPID
Parameter Project
Unit METRORAPID MÜNCHEN SHANGHAI SHANGHAI-HANGZHOU Maglev Line HAMBURG-BERLIN d So
Line end stopping Düsseldorf Hbf -Dortmund Hbf München Hbf -München Flughafen Longyang Road Station -Flughafen Pudong Longyang Road Station -Hangzhou East Station Hamburg Hbf - Berlin Lehrter Bf Berlin Papestraße -Budapest
Length km 79 37 30 163 292 884
Number of stations stations 7 2 2 6 5 10
Average distance between stops km 13.15 36.80 30.00 32.60 73.00 98.22
Maximum longitudinal slope %0 30 80 19 40 100 100
Design slopes %0 4 a 7 a 5 4 a 5 a 6
Relative length of bridges b % 3.00 5.80 1.24 3.00 1.70 c 1.20
Relative length of tunnels % 5.06 20.00 0.00 14.72d 0.62 0.80 e
Relative length of at grade guideway % 72.46 47.00 1.24 30.00 32.77 65.20
Reltive length of guideway elevated % 22.48 33.00 98.76 55.28 66.61 34.00
Annual volume of passenger traffic in both directions mil. pass. per year 34.37 7.86 10.00 33.00 10.50 6.10
Annual growth of the volume of passenger traffic per year % 4.5 3.5 4.3 6.2 3.2 1.6
The normative repayment of costs incurred (the validity period of the loan)f years 20 20 27 31 20 50g
Annual percent of the credit % 5.00 h 5.00 h 2.81 5.34 5.00 h 4.37 i
a Approximate data.
b Track structure on bridges laid on pillars. c Total length of 4.7 km [4].
d 24 km tunnel under the Huangpu River on a 32 km part between the Longyang Road Station and the airport Hongqiao [5].
e Five tunnels with total length: 6.3 km [6]. f From the moment of putting of the line into operation.
g For the overall design life of the project 50 years (of which 10 years account for design and construction work and 40 years on the phase of operation) on total costs was not the returned [6]. h Equals to the average discount rate: ~ 5% [7]. i 3 % - discount factor + 1.37 % - internal revenue [6].
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lengths varied from 1 to 15 km with a slope from 0 to 40 %o and goods traffic from 0.1 to 0.9 mil. t/year were examined (Fig. 4).
Abstract model for the generalized transport system
Model of concrete object
algorithm was- written йиг
MLX01
Mod d of concrete object was written for T RYVSRYHD
combinai principle of -optunuahoo. management о: tririE.pcit eve. tan
Ejesio nal transp ortatio в
м
Mod el lines
^ PPin^ - urd ]OL.E-distance tracsp citation
Project- und mo d eJ Icese
Passenger- and goods caffr Passat^- traffic
MLÏ01 airi TRAN&1AC
Ъф>г& speei optiniizati-nri т®.
MLX01 arÉ TRANSIAG
' грез; qp liinizjtic л
T RANSRAHD
vs.
mlxoi
2nd raihray
(ЪЪ1аЗ>
"rwariinl: specific travel tariff
Mod el of concrete abject
alïarilJmiwas wntt=n for
TRANSMAG
Model of concrete object algorithm was written ihr
TR^SSPROGRI SS
irt e'LiaJ principle of pptimization iiiaiujEiitJit rf transport ratam
Lопг-distance- and sub urb а с tra Dsp ortation
Modal lin es
Passenger traffic
-~4-'
LanEth c: lina:
3SO-4SOO Inn
Triri-c volumes:
1-25 mil p ass vear
Laaiin? ilope c£ line: 10%*
T RAN5MAG Ъфге ccsiçIej; op tiimstion
vs.
TRANSMAG фаг
ccsiipbi; op tiniizarijfi
FraE-Lt industrial
transportation
^
Mod el lines
И
Bulk good s traffic
LaiEtho: 1ût=-: 1-1? lai Taffic volui^s:
ОД - nriL t'year L ± aim г ilcpe of ltn=:
0-40%.
4
transprogre ss
ТЕ.
raik^\ cructc, cotn'ei'e; rcpeb pneuuatic- and hjd raulic- p ipeline ind IE trial transport jisteiUj
Invariant: total costs to no riua tiv e ternj о f rep arment
У
Fig. 4. Structure of the abstract model for the generalized transport system
For passenger transport, a comparison of Maglev system with conventional modes of transport the railway system was selected. These railway systems are operated or planned for the lines where in parallel concrete projects TRANSRAPID were investigated.
For goods traffic Maglev systems were compared with railway, trucks, conveyor, rope, pneumatic- and hydraulic- pipeline industrial transport systems.
In order to select the correct approaches for optimization of Maglev systems, the dependency of cost from the train maximum speed and the train configuration was studied
According to the results of the complex optimization, maglev-systems were evaluated by two criteria cost reduction and expansion of the application areas of Maglev systems compared to railway system (for passenger transport), as well as to other types of traditional transport (for freight industrial transport).
At the same time the limits of scopes of the application of TRANSRAPID and MLX01 were determined (Fig. 5).
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Fig. 5. Principles of the comparative analysis of Maglev systems
4. ANALYSIS AND ITS RESULTS 4.1 Analysis of complex optimization TRANSMAG
After conducting of the optimization of TRANSMAG [8] the value of the specific tariff was obtained for the transport of one passenger per one km, depending on traffic volume and line length (Fig. 6).
As a result of comparison of the tariffs of TRANSMAG before and after its complex optimization (Fig. 7) more than a double decline in the necessary traffic volume has been revealed at the fixed value of specific travel tariff 1,2 U.S. Cent per person*km (Table 2).
On this basis, it is necessary that at the fixed volume of annual traffic of 16 millions passengers per year, after complex optimization of TRANSMAG the size of travel tariff, after complex optimization of TRANSMAG, is approximately 2.11 times lower than the tariff before the system optimization (Table 3).
Thus, a 52.5 % decrease in the total expenses has been reached, decrease in capital investments and operational expenses defines economic efficiency of complex optimization of TRANSMAG.
More detailed structural analysis of expenses is presented in Table 4. It is showed, that the greatest part of their decrease constitutes of the operating costs.
The analysis shows a significant increase in efficiency of TRANSMAG as a result of its complex optimization [10].
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Fig. 6. Dependence of value of specific tariff of TRANSMAG on the traffic volume
and line length, after the optimization
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Fig. 7. Dependence of value of specific tariff of TRANSMAG on the traffic volume and line length, before the optimization [9]
Table 2. Determination of efficiency of complex optimization of TRANSMAG on the decline of traffic volume at the fixed value of travel tariffa
Parameter Unit Before opti-mazation After opti-mazation
Specific travel tariff U.S. Cent per person/ km 1.2
Normative term of exploitation of line, to repayment of the expenses Years 10
Low range of traffic volume, depending on length of line mill. pass. per year from 15-17 from 3-9.5
Arithmetical mean value of low range of traffic volume in both ends mill. pass. per year from 16 from 6.25
Coefficient of decline of necessary minimum volume of annual traffic for providing of self-repayment of the born charges to the normative term of exploitation of line x times 0 2.56
a Minimum necessary volume of annual traffic in both ends, for providing of self-repayment of the charges to the normative term of exploitation of line.
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Table 3. Determination of efficiency of complex optimization of TRANSMAG on the decline of value of the spared travel tariff at the fixed value of volume of annual traffic
Parameter Unit Before opti-mazation After opti-mazation
Volume of traffic mill. pass. per year 16
Range of tariffs at the set volume of annual traffic depending on length of line U.S. Cent per personxkm 1.1-1.3 0.8-0.53
Arithmetical mean value of tariff U.S. Cent per personxkm 1.2 0.57
Coefficient of decline of value of tariff at the set volume of annual traffic x times 0 2.11
Stake of the total resulted cost cutting to the normative term of exploitation of line % 0 52.5
Stake of capital investments from the total brought charges over to the normative term of exploitation of line % 27.48 47.39
Stake of total operating expenses from the total brought charges over to the normative term of exploitation of line % 72.52 52.61
Table 4. Structural determination of economic efficiency of complex optimization of TRANSMAG
Parameter Unit Capital investments Operating Costs
Reduction of costs at the expense of optimization % 18 66
Reduction of the initial resulted costs % 5 48
Reduction of the costs of the total economized sum % 10 91
Reduction of the mean annual operating costs of the initial resulted expenses % missed 5
Reduction of the mean annual operating costs of the total economized sum % missed 9
4.2 Analysis of optimization MLX01 and TRANSRAPID
For the calculation of MLX01 and TRANSRAPID, the design data on the TRANSRAPID lines were used. Fig. 8-15 present the results of simulation of MLX01 and TRANSRAPID.
Received: 01.10.2018. Revised: 30.10.2018. Accepted: 17.11.2018. This article is available under license K-aeiWXHn
Transportation Systems and Technology. 2018;4(3 suppl. 1):36-56 doi: 10.17816/transsyst201843s136-56
10
9 8
СЯ
METRORAPID MÜNCHEN SHANGHAI SHANGHAI- HAMBURG- SIC!
HANGZHOU BERLIN
(a) In the first year of operation
(b) In 50th year of operation
Fig. 8. Number of sections in train configuration
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Fig. 9. Travel time between the end stops per line
Fig. 10. Specific total capital investments per km length1
1 Without capital expenditures for the acquisition of additional rolling stock in connection with the increase in the volume of annual traffic.
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METRORAPID MÜNCHEN SHANGHAI SHANGHAI- HAMBURG- SIC!
HANGZHOU BERLIN
cs TRANSRAPID - model line (basic train configuration) ■ TRANSRAPID - model line (unlimited train configuration) s TRANSRAPID - project line (basic train configuration) a MLX01 - model line (unlimited Irain configuration) ŒBMLX01 - model line (basic train configuration)
Fig. 11. Specific operating costs for one passenger and one 1 km length1
110 T-—
j <-
METRORAPID MÜNCHEN SHANGHAI SHANGHAI- HAMBURG- SIC1
HANGZHOU BERLIN
s TRANSRAPID - model line (basic train configuration) a TRANSRAPID - model line (unlimited train configuration) ra TRANSRAPID - projcct line (basic train configuration) a MLX01 - model line (unlimited train configuration) m MLX01 - model line (basic train configuration)
Fig. 12. Total costs to time of repayment (payment of the loan)2
1 The model-project operating costs are variating. Operating costs vary depending on traffic volume and train configuration, consumed energy costs, the number of staff etc. Therefore the average value of operating costs is taken.
Also the calculation was performed according to the German projects from the condition of 0.053 EUR/personxkm for regional and 0.11 EUR/personxkm for the city-airport communications [11].
2 Taking into account capital expenditure for the purchase of additional rolling stock, in connection with the increase in the volume of annual traffic.
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METRORAPID MÜNCHEN SHANGHAI SHANGHAI- HAMBURG- SIC!
HANGZHOU BERLIN
N TRANSRAPID - model line (basic train configuration) f- TRANSRAPID - model line (unlimited train configuration) kj TRANSRAPID - project line (basic train configuration) M Railway transport
a MLXOI - model line (unlimited train configuration) m MLX01 - model line (basic train configuration)
Fig. 13. Specific tariff for transportation of 1 passenger per 1 km (the car of 2nd class)1
METRORAPID MUNCHEN SHANGHAI SHANGHAI- HAMBURG- SIC!
HANGZHOU BERLIN a TRANSRAPID - basic train configuration Bl TRANSRAPID - unlimited train configuration
Fig. 14. Economic effect to time of repayment of the total costs (validity period of loan),
of TRANSRAPID
1 Travel tariff are calculated taking into account factors of: the development experience of operating the new lines, discounting (reduction of costs at different times) and additional profit.
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The optimization model showed that, in parallel with the increase in speed performance, economic efficiency of the TRANSRAPID has increased on one third compared to its design data (Fig. 14).
These results are quite analogous with the value of economic efficiency, obtained in the optimization of TRANSMAG (52.5 %). This testifies the reliability of the results.
It also demonstrates that the increase of maximal number of sections per train compared with the base configuration, results in an additional decline of expenses of Maglev-systems by 7 percent on average.
4.3 Determination of the Application scopes between TRANSMAG and railway System
The area, characterizes by the specific travel tariff of the Ukrainian high speed train (1/2 U.S. Cent per personxkm), limits the scope of the effective application of TRANSMAG by the largest annual passenger traffic (Fig. 6, 7). By the optimization model of TRANSMAG, this low boundary moved up from 15-17 to 3-9.5 million passengers per year (Table 2) and thus two and half times enlarges the scope of its effective application.
4.4 Determination of the scope of TRANSPROGRESS in comparison with industrial bulk transport systems
For determination of the scope of effective application of the Maglev systems with traditional industrial transport systems for ore mining and metallurgical companies at transportation of friable loads, TRANSPROGRESS was chosen.
In this case the choice of the most effective transport system was carried out by minimum value of the total costs of line to the normative term of their repayment.
For TRANSPROGRESS, a abstract model of a generalized transport system was chosen. The method of calculation of the technical-economic indices [12] and preliminary optimization [13] were utilized. The technical-economic indices of other compared traditional industrial transport systems were executed via the methods of [14-15].
The scopes of effective application of the compared transport systems were determined in 3D co-ordinates, the axes of which correspond to the basic line parameters: length, size of leading slope and annual traffic of goods. Every point in the indicated co-ordinates system corresponds to most effective of compared transport systems.
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The results of calculations for seven conventional goods transport systems showed that the hydraulic pipeline appeared to be the most effective. After excluding from comparison the hydraulic pipeline transport system, the next effective systems are the TRANSPROGRESS, the rope transport system and the pneumatic-pipeline transport system (Fig. 15). In this case other belt systems appeared not competitive.
Further for the exposure of scopes of effective application of TRANSPROGRESS, the rope (Fig. 16), pneumatic pipeline (Fig. 17) and conveyor transport systems were consistently excluded from comparison.
Pneumatic pipeline transport system ( ) Pneumatic pipeline transport system ( )
(a) Right-side view (b) Left-side view
hydraulic pipeline transport system; pneumatic pipeline transport system; conveyor transport system; rope transport system; TRANSPROGRESS; trucks;
railway transport system.
Fig. 15. Comparison of TRANSPROGRESS with rope and pneumatic pipeline transport systems for transportation of bulk good in the conditions of ore mining and metallurgical
companies
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Piicumatic pipeline transport system ( )
hydraulic pipeline transport system; pneumatic pipeline transport system; conveyor transport system; rope transport system; TRANSPROGRESS; trucks;
railway transport system.
Fig. 16. Comparison of TRANSPROGRESS with pneumatic pipeline transport system for the transport for of ore mining and metallurgical companies
Conveyor transport system (■)
hydraulic pipeline transport system; pneumatic pipeline transport system; conveyor transport system; rope transport system; TRANSPROGRESS; trucks;
railway transport system.
Fig. 17. Comparison of TRANSPROGRESS with conveyor transport system for the transport
for of ore mining and metallurgical companies
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As it is seen, after exclusion from comparison of the conveyor transport system, the TRANSPROGRESS stay the most effective transport as compared to remaining railway and motor-car.
Thus, in all cases of application of TRANSPROGRESS, the most optimum for composition of its trains appeared configuration of continuous (closed) type that technically fully corresponds to the conditions of transport in ore mining and metallurgical enterprises.
Thus, on the example of complex optimization of TRANSPROGRESS, the competitiveness of application of the Maglev system in ore mining and metallurgical companies was grounded. Also possibility of determination of scopes of effective application of the compared traditional industrial transport systems was evidently presented (Fig. 18).
Railway transport system (■)
(a) Right-side view (b) Left-side view
hydraulic pipeline transport system; pneumatic pipeline transport system; conveyor transport system; rope transport system; TRANSPROGRESS; trucks;
railway transport system.
Fig. 18. Comparison of a conveyor belt system with trucks and a railway transport systems for the transport for of ore mining and metallurgical companies
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5. CONCLUSION
This study proved the validity of the technology of complex optimization of transport (for example Maglev systems). Its use will significantly reduce the cost of implementation of various transport systems and expand the scope of their effective application (Fig. 19).
Fig. 19. Determination scheme of the scopes of effective application of Maglev systems
The results of theoretical researches presented in this work are intended above all for the exposure of basic directions of optimization of transport systems.
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Information about the authors: Lascher Arkadij, Dipl.-Ing, PhD-student; E-mail: [email protected]
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Witt Michael, Dipl. Wi.-Ing; E-mail: [email protected]
Frishman Evgeni, Dr.-Ing; E-mail: [email protected]
Umanov Mark, Dr.-Ing, Senior scientific researcher; E-mail: [email protected]
To cite this article:
Lascher A, Witt M, Frishman E, Umanov M. Results of the Complex Optimization of Maglev. Transportation Systems and Technology. 2018;4(3 suppl. 1):36-56. doi: 10.17816/transsyst 201843s136-56
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