EMR 13 Lille Sept. 213 Summer School EMR 13 Energetic Macroscopic Representation «OPTIMAL ENERGY MANAGEMENT BY EMR AND META-HEURISTIC APPROACH FOR MULTI-SOURCE ELECTRIC VEHICLES» Dr. João Pedro TROVÃO, Prof. Paulo Pereirinha INESC Coimbra, Polytechnic Institute of Coimbra, PORTUGAL jtrovao@isec.pt Dr. Walter LHOMME, Prof. Alain BOUSCAYROL L2EP, University Lille1, MEGEVH network, FRANCE
- Outline - 1. Introduction Environment and Social Consideration Approach used until now 2. A New Case Study 3. EMR of Studied Topology Global EMR model Inversion-based control structure 4. Energy Management Strategy Dynamic search space restriction process Meta-heuristic decisions 5. Simulations Results 6. Conclusions and Future Works 7. Biographies and References 2
EMR 13 Lille Sept. 213 Summer School EMR 13 Energetic Macroscopic Representation «Environmental and Social Constrains»
- Environmental and Social Constraints - 4 Transports sector accounted for 6.3% OF WORLD OIL CONSUMPTION (25), against 45.4% (1973); FUEL CONSUMPTION increasing leads to FORECAST OIL SHORTAGE AND PRICE RISE (~US$15 at July 28); Mass utilization of ICE VEHICLES increases pollution emissions: Greenhouse Gas emissions
- Environmental and Social Constraints - 5 ELECTRIC VEHICLES are the key components to SUSTAINABLE MOBILITY and world s future (reducing energy consumption and GEE emission). BARRIERS Energy storage in mobile systems is still a problem 1 years old problem! BATTERIES (best suitable energy storage for vehicles): expensive, heavy, bulky, low specific energy and/or power, and limited cycles-life;
- Approach used @ Coimbra until Now - 6 HYBRIDIZATION OF TWO SOURCES: HSE AND HSP SOURCES (NIMH BATTERIES AND SUPERCAPACITORS); COMMON DC LINK VOLTAGE COUPLING; PARALLEL HYBRID TOPOLOGY. ELECTRICAL POWERTRAIN BASED ON VSI, IM AND A MECHANICAL TRANSMISSION
TRADITIONAL APPROACH: - Approach used @ Coimbra until Now - Voltage of the DC Link Stabilization by the HSE Decoupling Method is used to compensate the contribution of HSP Source decoupling method 7 ENERGY MANAGEMENT LAYER: To give the HSP source current reference to the control layer
EMR 13 Lille Sept. 213 Summer School EMR 13 Energetic Macroscopic Representation «A New Case Study»
L2EP ELECTRIC VEHICLE: Tazzari Zero Neighborhood Electric Vehicle (NEV) Motor power: 15 kw; Lithium-ion: 24 x 5.6 = 134.4 kg Driving Range: 14 km Maximum speed: 1 km/h; Maximum Aceleration: -5 km/h < 5 s - Electric Vehicle Characteristics - 9
- Proposed Topology - 1 NEW TOPOLOGY CONFIGURATION: Active parallel topology with Batteries and Supercapacitors; A DC/DC converter per source is used; The input voltage of these converter can be different and the output can be adjustable to a shared DC bus supplying the traction system.
CONSIDERED SOURCES: NIMH BATTERIES - Sources Characteristics - 11 TOTAL WEIGHT: 48 KG SUPERCAPACITORS TOTAL WEIGHT: 44.5 KG
12 «EMR of Studied Topology»
- EMR of Studied Topology - 13 Energetic Macroscopic Representation (EMR) Systemic Approach, Energy Exchanges, Decomposition of Complex System Control Structure directly deduced from a Graphical Symmetry of the EMR Models (Inversion Based Control) Top-down Approach
- Global EMR Modelling- 14
- EMR Modelling- 15 or
- EMR Modelling- Driving Cycle profile; 16 Velocidade [km/h] 45 4 35 3 25 2 15 1 5 1 2 3 4 5 6 v(t) Modelling the Environment; Modelling the Chassis; Modelling the Gearbox; Modelling the Electric motor and its controller; Modelling the Parallel coupling; Modelling the DC bus.
TUNING PATHS: - Inversion-Based Control deduced by EMR - 17 FEEDING SYSTEM CONTROL: POWERTRAIN CONTROL:
- Command Structure - 18 KD=f(Pdem, SoCbat, SoCsc, Vbat, Vsc,)
19 «Energy Management Strategy»
- Energy Management Strategy - 2 EV Management Strategy Layer EV Control Layer Objective: Search of an optimal energy flow leading to an overall maximization of batteries SoC, while keeping SCs SoC and available energy of both systems at required levels (in the real-time). The proposed architecture has been divided in two management levels (strategic and tactical) and one operational level (control layer). The energy management is responsible for strategic planning, and the power management for action planning. The operational level controls the DC-DC converters, performing the actions defined by the upper levels.
- Energy Management Strategy - MULTI-LEVEL ENERGY MANAGEMENT: AN INTEGRATED RULE-BASED META-HEURISTIC APPROACH 21 Dynamic search space restriction process 21
- Energy Management Strategy - MULTI-LEVEL ENERGY MANAGEMENT: DYNAMIC SEARCH SPACE RESTRICTION PROCESS Based on statistics and past experience, two classes of rules have been defined (weak and medium rules); For instance: if the energy is under a specified threshold, an exchange of energy between the sources must be considered by the power management level. 22
- Energy Management Strategy - 23
24 «Simulations Results»
Speed [km/h] 6 4 2 ref. Tazzari - Results: ECE 15 and Road Slope of 2.5 % - First test: initial sources SoC of 9% for the SCs and for the batteries; I Total [A] 4 3 2 1 25 I T-ref I T 2 4 6 8 1 12 14 16 18 2-1 2 4 6 8 1 12 14 16 18 2 Power [W] 1 5 P dem P Bat P SC I Bat [A] 6 4 2 I bat-ref I bat -5 2 4 6 8 1 12 14 16 18 2-2 2 4 6 8 1 12 14 16 18 2 Voltage [V] 36 34 32 3 V dclink-ref V dclink 28 2 4 6 8 1 12 14 16 18 2 I SC [A] 15 1 5-5 I SC-ref -1 I SC -15 2 4 6 8 1 12 14 16 18 2 Load Current [A] 4 3 2 1-1 2 4 6 8 1 12 14 16 18 2 Time [s] SoC [%] 1 8 6 SoC bat SoC SC 4 2 4 6 8 1 12 14 16 18 2 Time [s]
Speed [km/h] 6 4 2 ref. Tazzari - Results: ECE 15 and Road Slope of 2.5 % - Second test: initial sources SoC of 4% for the SCs; I Total [A] 4 3 2 1 I T-ref I T 26 2 4 6 8 1 12 14 16 18 2-1 2 4 6 8 1 12 14 16 18 2 Power [W] P dem 1 P Bat P SC 5-5 2 4 6 8 1 12 14 16 18 2 I Bat [A] 6 4 2-2 2 4 6 8 1 12 14 16 18 2 I bat-ref I bat Voltage [V] 36 34 32 3 V dclink-ref V dclink 28 2 4 6 8 1 12 14 16 18 2 I SC [A] 15 1 5-5 -1 I SC-ref I SC -15 2 4 6 8 1 12 14 16 18 2 4 1 Load Current [A] 3 2 1 SoC [%] 8 6 SoC bat SoC SC -1 2 4 6 8 1 12 14 16 18 2 Time [s] 4 2 4 6 8 1 12 14 16 18 2 Time [s]
- Results: ARTEMIS and Road Slope of 2.5 % - Third test: initial sources SoC of 4% for the SCs; 27 6 4 Speed [km/h] 4 2 ref. Tazzari I Total [A] 2 I T-ref I T 2 4 6 8 1 12 14 16 18 2-2 2 4 6 8 1 12 14 16 18 2 Power [W] P dem 1 P Bat P SC 5-5 2 4 6 8 1 12 14 16 18 2 I Bat [A] 6 4 2-2 2 4 6 8 1 12 14 16 18 2 I bat-ref I bat Voltage [V] 36 34 32 3 V dclink-ref V dclink 28 2 4 6 8 1 12 14 16 18 2 I SC [A] 15 1 5-5 -1-15 2 4 6 8 1 12 14 16 18 2 I SC-ref I SC 4 1 Load Current [A] 2 SoC [%] 8 6 SoC bat SoC SC -2 2 4 6 8 1 12 14 16 18 2 Time [s] 4 2 4 6 8 1 12 14 16 18 2 Time [s]
Speed [km/h] 5 4 3 2 1 ref. Tazzari «OPTIMAL ENERGY MANAGEMENT BY EMR AND META-HEURISTIC APPROACH 5 1 15 2 25 3 35 - Results: NYCC and Road Slope of 2.5 % - Fourth test: initial sources SoC of 2% for the SCs; I Total [A] 6 4 2-2 I T-ref I T 28 5 1 15 2 25 3 35 Power [W] 2 x 14 1 P dem P Bat P SC I Bat [A] 5 4 3 2 1 I bat-ref I bat -1 5 1 15 2 25 3 35 5 1 15 2 25 3 35 Voltage [V] 36 34 32 3 V dclink-ref V dclink 28 5 1 15 2 25 3 35 I SC [A] 2 I SC-ref 1 I SC -1-2 5 1 15 2 25 3 35 6 1 Load Current [A] 4 2 SoC [%] 8 6 4 SoC bat SoC SC -2 5 1 15 2 25 3 35 Time [s] 2 5 1 15 2 25 3 35 Time [s]
29 «Conclusions and Future Works»
- Conclusions - 3 EMR concept allows a systemic study of the Batteries/SCs hybrid system; This approach leads to: A direct and systematic control structure definition; A better structure of the degrees of freedom to define the EMS. The proposed EMS combines an energy management level, implemented by a Dynamic Restricted Search Space, and a power management level, to determine the Best Power Sharing Solution under strategic orientations issued by the energy management level. The power sources usage are optimized, the requirements to the batteries are reduced, SCs are used in high peaks and high load fluctuations, and also stores all regenerative energy. These increase the EV driving range with a relatively low power battery bank when compared to the global requested power. The simulation results demonstrate that the unified EMS based on EMR is very effective to compute an online power sharing without knowledge of the future power demanded.
- Future Works - 31
32 «BIOGRAPHIES AND REFERENCES»
- Authors - 33 Dr. João Pedro Trovão Polytechnic Institute of Coimbra, INESC Coimbra, APVE, Portugal Associate Professor since 213 PhD in Electrical Engineering at University of Coimbra (213) Research topics: EVs and HEVs, renewable energy, energy management and power quality Prof. Paulo PEREIRINHA Polytechnic Institute of Coimbra, INESC Coimbra, APVE, Portugal Coordinator Professor since 28 PhD in Electrical Engineering at University of Coimbra (25) Research topics: Electrical machines, EVs and HEVs, finite elements, and renewable energies
- Authors - 34 Dr. Walter LHOMME University Lille 1, L2EP, MEGEVH, France Associate Professor since 28 PhD in Electrical Engineering at University Lille1 (27) Research topics: EMR, Electric and Hybrid Vehicles, Energy Storage Subsystem Prof. Alain BOUSCAYROL University Lille 1, L2EP, MEGEVH, France Coordinator of MEGEVH, French network on HEVs PhD in Electrical Engineering at University of Toulouse (1995) Research topics: EMR, HIL simulation, tractions systems, EVs and HEVs
- References - 35 [1] Trovao, J.P.F.; Santos, V.D.N.; Pereirinha, P.G.; Jorge, H.M.; Antunes, C.H., "A Simulated Annealing Approach for Optimal Power Source Management in a Small EV," Sustainable Energy, IEEE Transactions on, vol.pp, no.99, pp.1,1, doi: 1.119/TSTE.213.2253139; [2] João P. Trovão, Paulo G. Pereirinha, Humberto M. Jorge, Carlos Henggeler Antunes, A multilevel energy management system for multi-source electric vehicles An integrated rule-based meta-heuristic approach, Applied Energy, Volume 15, May 213, Pages 34-318, ISSN 36-2619, http://dx.doi.org/1.116/j.apenergy.212.12.81; [3] Allègre, Anne-Laure; Bouscayrol, Alain; Trigui, Rochdi: 'Flexible real-time control of a hybrid energy storage system for electric vehicles', IET Electrical Systems in Transportation,, 3, (3), p. 79-85, DOI: 1.149/iet-est.212.51 IET Digital Library, http://digitallibrary.theiet.org/content/journals/1.149/iet-est.212.51; [4] Allègre AL, Trigui R, Bouscayrol A. Different energy management strategies of Hybrid Energy Storage System (HESS) using batteries and supercapacitors for vehicular applications. In: 6th IEEE vehicle power and propulsion conference, VPPC 21, Lille, France; September 1 3, 21; [5] P. Barrade, Y. Brunet, Supercapacitors : Principles, Sizing, Power Interfaces and Applications, Energy Storage, 211, p. 217-241, London: ISTE Ltd, 211, ISBN: 978-1- 84821-183-4; [6] W. Lhomme, R. Trigui, A. Bouscayrol, P. Delarue, B. Jeanneret, F. Badin, Inversion-based control of a vehicle with a clutch using a switched causal modelling, International Journal of Systems Science, February 211, vol. 42, no. 2, p. 319-334; [7] Lhomme W, Delarue P, Barrade P, Bouscayrol A, Rufer A. Design and Control of a supercapacitor storage system for traction applications. In: Industry applications conference, 25. Fourtieth IAS annual meeting conference record of the 25, vol. 3; 2 6 October 25. p. 213 2.
«Title of the presentation» Thank you We look forward to hosting you in Coimbra! 36