«EMR of an Electric Vehicle»

Transcription

1 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

2 - Outline 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

3 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Introduction»

4 - Introduction- 4 In 2010, at EU, 28.8 % of the total emissions of carbon dioxide (CO 2 ) 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 vehicles one-month monitored.

5 - 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. 5

6 - Introduction- 6 Electric minibuses use lead-acid batteries.

7 Average daily consumption - Introduction- Average specific consumption 70 kwh / 100 km Total average consumption 123 kwh / 100 km 7 Energy for traction Losses in charging in kw h

8 - Introduction- 8 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

9 - Introduction- 9 Energetic Macroscopic Representation : - highlights the energetic properties of this subsystem; - uses integral causality that defines time-dependency of accumulation elements; - take in account with interaction between the system and the environment; - gives feasible results for technical and economic studies of batteries utilization

10 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Electric Minibus Characterization»

11 - 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. 11 Variable Symbol Value Units Vehicle mass (without bat/sc) 4285 kg Rolling resistance coefficient Gravity acceleration 9.81 m/s 2 Air 20ºC kg.m -3 Aerodynamic drag coefficient Vehicle front area m 2 Wheels radius m Gearbox transmission ratio Gearbox transmission efficiency 90 %

12 - Electric Minibus Characterization- 12 Energy storage system is composed by two lead-acid batteries (modules) connected in series, each one of 36 V, 585 Ah and 750 kg Variable Symbol Value Units Lead-acid: data for each 36V battery module Battery Power C) [ - 2.1, 10.5 ] kw Battery SoC Limits* [ 0.2, 1 ] - Min. Battery open-circuit voltage V Battery no-load voltage drop 2.55 V Max. Battery open-circuit voltage 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 -

13 - Electric Minibus Characterization- 13

14 - Electric Minibus Characterization- 14

15 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «GPS Data»

16 - GPS Data - 16 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

17 - GPS Data - 17

18 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Minibus EMR»

19 - Minibus EMR - 19 bat i bat v bat Batteries i bat T em v bat m Electric machine T em T gear m gear T bk gear Brake system

20 - Minibus EMR - 20 T gear F tr gear v EV Gearbox and Wheels F tr v EV v EV F env. Chassis v EV Env F env. Environment

21 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Minibus EMR Control and Strategy»

22 Bat. Electrical Machine - Minibus EMR - Control and Strategy - Brake system Gearbox and Wheels Chassis Env. 22 bat i bat T em T gear F tr v EV Env. v bat T em_r m T bk gear v EV F env. brake gear T bk_r T gb_r F tr_r v EV_r K D Strategy

23 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Simulations Current batteries»

24 I Bat [A] V Bat [A] Speed [km/h] SoC [%] «Title of the presentation» - Simulations Current Batteries ref. Bus Time [s]

25 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Simulations New batteries»

26 Li-Ion batteries alternative «Title of the presentation» - Simulations New Batteries - 26 Variable Symbol Value Units Li-Ion: data for each 3.2V module (Winston Battery WB-LYP700AHA) Battery Power (@0.5 C) [ , 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 -

27 SoC [%] V Bat [A] I Bat [A] Speed [km/h] «Title of the presentation» - Simulations Current Batteries ref. Bus Time [s]

28 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Conclusions and Perspectives»

29 - 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

30 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «REFERENCES»

31 - References - 31 [1] EU Transport in Figures Statistical Pocketbook 2013, European Comission, [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, [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, [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, (in Portugese) [5] EMR website, Energetic Macroscopic Representation, [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, [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, [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, [9] Mayet, C.; Horrein, L.; Bouscayrol, A; Delarue, P.; Verhille, J.-N.; Chattot, E.; Lemaire-S , 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

32 EMR 15 Lille June 2015 Summer School EMR 15 Energetic Macroscopic Representation «Thank you»