« EMR of an Electric Vehicle · 2015-07-02 · EMR’15, Lille, June 2015 4 « Title of the presentation » - Introduction- In 2010, at EU, 28.8 % of the total emissions of carbon

EMR’15

Lille

June 2015

Summer School EMR’15

“Energetic Macroscopic Representation”

« EMR of an Electric Vehicle»

Nuno FARIA, Prof. Paulo PEREIRINHA

INESC Coimbra, Portugal

Prof. João P. TROVÃO

University of Sherbrooke, Canada

EMR’15, Lille, June 2015 2

« Title of the presentation »

- Outline -

1. Introduction

2. Electric Minibus Characterization

3. GPS Data

4. Mini bus EMR

- Control and Strategy

5. Simulation Results

- Current bateries

- New batteries

6. Conclusion and Perspectives

EMR’15

Lille

June 2015



« Introduction »



- Introduction-

In 2010, at EU, 28.8 % of the total emissions of carbon dioxide (CO2)

equivalent are from transportation sector.

Transport is the only major sector in the EU where greenhouse gas

emissions are still rising.

Road transportation alone accounted for 20.7 % of the 2010 emissions

with an increase of around 22.5% between 1990 and 2010

It would be bigger if there was not an economic crisis in the last years, as

the increase between 1990 and 2007 was of 29 %.

Recent study conducted in the province of Modena, Italy, with average trip

length between 5 and 20 km, shows that electric mobility can be used on

more than 80 % of the trips of the 16000 vehicles one-month monitored.



- Introduction-

Coimbra has a history of more than one hundred years of electric vehicles

for public transportation. First, in 1911, over rails, with several tram lines

and after, in 1947, with trolley buses. Nowadays there are still 2 lines of

trolleybuses and one line of electric minibus in the historical center.



- Introduction-

Electric minibuses use lead-acid batteries.



- Introduction-

Average daily consumption

Losses in charging

Energy for

traction

Average specific consumption

70 kWh / 100 km

Total average consumption

123 kWh / 100 km

in kWh



- Introduction-

Batteries evolution in terms of specific energy, peak currents and no-memory

effect (e.g. Li-Ion)

Prepare the purchase of new batteries to replace the existing ones that are

reaching the end of life



- Introduction-

- gives feasible results for technical and economic studies of

batteries utilization

Energetic Macroscopic Representation :

- highlights the energetic properties of this subsystem;

- take in account with interaction between the system and the

environment;

- uses integral causality that defines time-dependency of

accumulation elements;

EMR’15

Lille

June 2015



« Electric Minibus Characterization »



- Electric Minibus Characterization-

TECNOBUS Gulliver U520 for 20 passengers plus driver with a DC motor

24.8 kW and maximum torque of 235 Nm at 950 rpm. Minibuses fully loaded

weight 6035 kg, have 6.5 h of autonomy and maximum velocity of 33 km/h.

Variable Symbol Value Units

Vehicle mass (without bat/SC) 4285 kg

Rolling resistance coefficient 0.035 -

Gravity acceleration 9.81 m/s2

Air density @ 20ºC 1.223 kg.m-3

Aerodynamic drag coefficient 0.7 -

Vehicle front area 5.693 m2

Wheels radius 0.365 m

Gearbox transmission ratio 4.37 -

Gearbox transmission efficiency 90 %




Energy storage system is composed by two lead-acid batteries (modules)

connected in series, each one of 36 V, 585 Ah and 750 kg


Lead-acid: data for each 36V battery module

Battery Power (@0.5 C) [ - 2.1, 10.5 ] kW

Battery SoC Limits* [ 0.2, 1 ] -

Min. Battery open-circuit voltage 36.65 V

Battery no-load voltage drop 2.55 V

Max. Battery open-circuit voltage 39.20 V

Battery internal resistance 11.7 mΩ

Battery mass 750 kg

Number of battery modules in series 2 -

Num. of battery modules in parallel 1 -







EMR’15

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June 2015



« GPS Data »



- GPS Data -

Application for Android installed in a mobile phone with GPS built-in;

The coordinates in WGS84 and altitude values are first stored in a website and

after exported to a comma separated value (*.csv) file to be introduced in

Matlab/Simulink simulation;

Later calculations allowed extract the speed, slope and distance parameters

required for the EMR



- GPS Data -

EMR’15

Lille

June 2015



« Minibus EMR »



- Minibus EMR -

Electric machine

Brake system

Batteries

ibat

vbat

ibat

vbat

Tem

m

Tem

m

Tgear

gear

Tbk

gear

bat



- Minibus EMR -

Gearbox and

Wheels

Chassis

Environment

Tgear

gear

Ftr

vEV

Ftr

vEV

vEV

Fenv.

vEV

Fenv.

Env

EMR’15

Lille

June 2015



« Minibus EMR – Control and Strategy »



- Minibus EMR - Control and Strategy -

bat

Bat. Electrical

Machine

Gearbox

and

Wheels Env. Chassis

ibat

vbat

Tem

m

Tem_r

vEV

Fenv.

Ftr

vEV

Env.

Ftr_r vEV_r

Tgear

gear

Tgb_r

brake

Strategy

KD

Tbk

gear

Tbk_r

Brake

system

EMR’15

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June 2015



« Simulations – Current batteries »



- Simulations – Current Batteries -

0 200 400 600 800 1000 1200 1400 16000

10

20

30

Sp

ee

d [

km/h

]

ref.

Bus

0 200 400 600 800 1000 1200 1400 1600

0

500

1000

I Ba

t [A

]

0 200 400 600 800 1000 1200 1400 160050

60

70

80

VB

at [

A]

Time [s]

0 1 2 3 4 5 6 7

40

50

60

70

80

90

So

C [

%]

0 1 2 3 4 5 6 70

10

20

30

40

50

60

Dis

tan

ce

[km

]

Time [h]

EMR’15

Lille

June 2015



« Simulations – New batteries »



- Simulations – New Batteries -


Li-Ion: data for each 3.2V module (Winston Battery WB-LYP700AHA)

Battery Power (@0.5 C) [ - 25.8, 25.8] kW

Battery SoC Limits [ 0.2, 1 ] -

Min. Battery open-circuit voltage 2.8 V

Battery no-load voltage drop 1.2 V

Max. Battery open-circuit voltage 4 V

Battery internal resistance 0.2 mΩ

Battery mass 21 kg

Number of battery modules in series 23 -

Num. of battery modules in parallel 1 -

Li-Ion batteries alternative



- Simulations – Current Batteries -

0 200 400 600 800 1000 1200 1400 16000

10

20

30

Sp

ee

d [

km/h

]

ref.

Bus

0 200 400 600 800 1000 1200 1400 1600

0

200

400

600

I Ba

t [A

]

0 200 400 600 800 1000 1200 1400 160085

86

87

88

89

90

VB

at [

A]

Time [s]

0 1 2 3 4 5 6 7

40

50

60

70

80

90

So

C [

%]

0 1 2 3 4 5 6 70

10

20

30

40

50

60

Dis

tan

ce

[km

]

Time [h]

EMR’15

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June 2015



« Conclusions and Perspectives »



- Conclusions -

- First EMR for this minibus

- Results are according with Operator’s information

- Future refinement of EMR

- Tool for technical and economic analysis and decision

EMR’15

Lille

June 2015



«REFERENCES »



- References -

[1] EU Transport in Figures Statistical Pocketbook 2013, European Comission, 2013.

[2] Michele De Gennaro, Elena Paffumi, Harald Scholz and Giorgio Martini, “Analysis and assessment of the electrification of urban road transport based on real-life mobility data”, 27th International Electric Vehicle Symposium & Exhibition, EVS27, Spain, November 17-20, 2013.

[3] Kento Tanaka, Shota Kimura, Yuto Miyasaka, Toshio Hirota, Yushi Kamiya and Yasuhiro Daisho, “Design, Manufacture, and Environmental Sustainability Evaluations of Advanced Electric Medium Duty Bus “WEB for Suntory”, 27th International Electric Vehicle Symposium & Exhibition, EVS27, Spain, November 17-20, 2013.

[4] Luís Santos, “Os veículos eléctricos na alta de Coimbra”, Workshop Combustíveis e Veículos Alternativos – Práticas Correntes e Futuras Linhas de Orientação Politíca para o Transporte de Passageiros (Projecto Alter-Motive), Lisbon, October 27, 2010. (in Portugese)

[5] EMR website, Energetic Macroscopic Representation, www.emrwebsite.org.

[6] João P. Trovão, Alain Bouscayrol, Felipe Machado, Walter Lhomme “Hierarchical Management Structure of a Battery/SuperCapacitor System For na EV Using Energetic Macroscopic Representation” 11th International Conference on Modeling and Simulation of Electric Machines, Converters and Systems, ElectriMACS, Spain, May 19-22, 2014.

[7] João P. Trovão, Victor D. N. Santos, Paulo G. Pereirinha, Humberto M. Jorge, Carlos Henggeler Antunes, “Comparative Study of Different Energy Management Strategies for Dual-Source Electric Vehicles”, 27th International Electric Vehicle Symposium & Exhibition, EVS27, Spain, November 17-20, 2013.

[8] T. Letrouvé, A. Bouscayrol, W. Lhomme, N . Dollinger, F. Mercier Calvairac, “Different models of a traction drive for an electric vehicle simulation”, Vehicle Power and Propulsion Conference (VPPC), 2010 IEEE Lille, France, September 1-3, 2010.

[9] Mayet, C.; Horrein, L.; Bouscayrol, A; Delarue, P.; Verhille, J.-N.; Chattot, E.; Lemaire-Semail, B., “Comparison of Different Models and Simulation Approaches for the Energetic Study of a Subway”, IEEE Transactions on Vehicular Technology, vol.63, no.2, pp.556,565, Feb. 2014.

EMR’15

Lille

June 2015



« Thank you »

Documents

« EMR of an Electric Vehicle · 2015-07-02 · EMR’15, Lille, June 2015 4 « Title of the presentation » - Introduction- In 2010, at EU, 28.8 % of the total emissions of carbon