«EMR, inversion-based control and energy …...EMR’14, Coimbra, June 2014 4 « EMR, IBC and energy management of a Hybrid Locomotive» • starting 2004, • more than 750 researchers

EMR’14CoïmbraJune 2014

Summer School EMR’14“Energetic Macroscopic Representation”

««EMR, inversionEMR, inversion--based control and based control and energy management of a Hybrid energy management of a Hybrid

LocomotiveLocomotive»»

Dr. Jérôme BAERT, Dr. Samir JEMEI, Prof. Daniel HISSEL, Samuel HIBON, Dominique HEGY

FEMTO-ST / FCLAB, University of Franche-Comte, FranceALSTOM Transport, Belfort, France

EMR’14, Coimbra, June 20142

«« EMR, IBC and energy management of a Hybrid LocomotiveEMR, IBC and energy management of a Hybrid Locomotive»»

- Outline -

1. Introduction

2. Modeling of the Hybrid Electric Locomotive

3. Fuzzy Logic Energy Management Strategy

4. Conclusions



IntroductionIntroduction



• starting 2004,• more than 750 researchers & engineers• energy, micro-nano systems and time based

frequency research,• research excellence (AERES rank A+ -

French top rank).

• systems, equipments and services for the railway market,

• n°1 in the trams and subways market,• n°2 in the high speed trains market,• leader in diesel and electric locomotives

business.

- Partners of the project -



- FEMTO-ST former research works based on EMR (transport) -



- Context & problematic -

• Focus : freight locomotives• 90% of time used at less than 50% of maximal power (diesel generator set)

Interest for hybridization ??



- Existing solutions -

• Series architecture,• 1.3 MW engine,• 6 DC traction motors,• LiFeP04 batteries.

Chinese Dongfeng 7G

• diesel hybrid• switcher locomotive platform,• 250 kW PEM Fuel Cell,• valve regulated lead-acid batteries.

American Railpower Green Goat

• Series architecture, diesel engine,• NiCd batteries,• ultra-capacitors, PEM fuel cell,• 4 electric engines

French Plathee Project



- Considered case study -

• 60% less particles• 40% less NO• 15% less maintenance



Modeling of the Hybrid Electric Modeling of the Hybrid Electric LocomotiveLocomotive

BatteriesBatteriesUltraUltra--capacitorscapacitors

Diesel driven generator setDiesel driven generator setGlobal architectureGlobal architecture



- Global architecture of the considered locomotive -



- Modelling & PCS / batteries -

Hoppecke FNC-A 170 XR2 – NiCd Accumulator

Nominal voltage (V) 1.2

Nominal current (A) 34

Capacity (Ah) 170

Electrolyte Potassium hydroxide (KOH)

The model takes into account:•the voltage dynamics according to current variation,•the polarization voltage to model the non linear variations of the OCV with the SOC,•the exponential zone voltage to consider the NiCd hysteresis phenomenon.

•Charging phase :

•Discharging phase :

[REF] O. Tremblay and L.-A. Dessaint, Experimental Validation of a Battery Dynamic Model for EV Applications, World Electric Vehicle Journal, Vol. 3 - ISSN 2032-6653 - © 2009 AVERE.




Battery cell modelSmoothing inductance

DC/DC converter

Coulomb counter

Batteries




Experimental results (C5 rate tests)

-50°C



- Modelling & PCS / ultracapacitors -

second range minute range

[REF] L. Zubieta and R. Bonert, Characterization of double-layer capacitors for power electronics applications, IEEE Transactions on Industry Applications, Vol. 36, No. 1, pp. 199 205, 2000.



- Modelling & PCS / ultracapacitors -

[REF] L. Zubieta and R. Bonert, Characterization of double-layer capacitors for power electronics applications, IEEE Transactions on Industry Applications, Vol. 36, No. 1, pp. 199 205, 2000.

U-caps



- Modelling & PCS / diesel engine -

[REF] Verdonck, N., Chasse, A., Pognant-Gros, P. and Sciarretta, A. , Automated Model Generation for Hybrid Vehicles Optimization and Control, Oil Gas Sci. Technol. Rev. IFP, Vol. 65, No. 1, pp. 115-132, 2010.

Fuel Air

Air

EMR




Control of delivered mechanical power through : •Incoming air flow•Incoming fuel flow

Fuel Air

Air

Naturally aspirated diesel engine




Salient pole synchronous electrical generator

Separated excitationbranch model

Electromechanical conversion

branch model

Estimation of:•electromotive force•load torque

DC source

DC bus




Complete diesel-driven generator set

Naturally aspirated diesel engine Salient pole synchronous machine

[REF] J. Baert, S. Jemei, D. Chamagne, D. Hissel, S. Hibon, and D. Hegy, “Energetic Macroscopic Representation of a Naturally Aspirated Engine coupled to a salient pole synchronous machine”, 8th IFAC PPPSC Conference, Vol. 8, No. 1, pp. 435-440, Toulouse, France, 2012.

Fuel Air

Air

DC source

DC bus



- Modelling & PCS / global architecture -

(1) Diesel drivengenerator set

(2) Batteries

(3) Ultracapacitors

(4) Braking rheostat

(5) Bus capacitance

(6) Energy ManagementStrategy

(1)

(2) (3)

(4)

(5)

(6)

[REF] J. Baert, S. Jemei, D. Chamagne, D. Hissel, S. Hibon, and D. Hegy, “Modeling and Energy Management Strategies of a Hybrid Electric Locomotive“, IEEE Vehicle Power and Propulsion Conference (VPPC), pp.990-995, Seoul, Korea, 2012.



Fuzzy Logic Fuzzy Logic Energy Management StrategyEnergy Management Strategy

Structure of the EMSStructure of the EMSFuzzy Logic SupervisorFuzzy Logic Supervisor

ResultsResults



- Structure of the EMS -

Goal?To share the power required on a given driving cycle performed by the locomotive between the different on-board sources, taking into account their own specifications.




Constraints ?

Ultra-capacitors NiCd BatteriesCharging time Second range Hour range

Discharging time Second range Hour rangeEfficiency 85% to 98% 70% to 85%

Power density (W/kg) 104 <103

Energy density (Wh/kg) 1 to 10 10 to 100

Life cycles 105 to 106 103




Constraints ?

Ultra-capacitors:•Limitation of the State Of Charge (SOC) between 50% and 100%,•control of the SOC according to the speed of the vehicle to use ultra-capacitors like a buffer.

Batteries:•Limitation of the State Of Charge (SOC) between 70% and 90%,•control of the SOC according to the acceleration of the vehicle to avoid an early discharge in the case of a cruise speed and to maintain the SOC at maximum level.

minmaxmaxref ucuc

max

vehucuc SOCSOC

vvSOCSOC

minmaxmaxref bbmax

vehbb SOCSOC

vvSOCSOC attattattatt




Diesel driven generator set:•Use of a Fuzzy Logic Supervisor to determine the power delivered by this source•Supply the low frequencies of the power mission with the batteries

IF is N

AND is P

THEN is P



- Interval type-2 fuzzy logic -

Advantages :•Higher robustness / ability of management of uncertainty•Higher robustness versus driving cycle

-40 -30 -20 -10 0 10 20 30 400

0.2

0.4

0.6

0.8

1

x

y

Here : •7 linguistic variables defined by trapezoid, triangular and Interval membership functions: NH, NM, NL, Z, PL, PM, PH•Optimization of their positions by genetic algorithm in order to minimize the fuel consumption of the diesel-driven power generator




Power distribution (zoom on an part of a driving cycle)



ConclusionsConclusions




EMR enables : •Efficient power-flow-oriented modeling of various transportation vehicles•Successful management of multi-physics systems•Successful implementation of inversion based control•easy and efficient definition of power supervision strategies•Easy on-line validation (from simulation to first experimental implementation)

EMR side-features :•Easy management of multi-physical systems & different expert engineers•Re-use of the developed models (“physical causality” “inside”)



International summer school

Documents

«EMR, inversion-based control and energy …...EMR’14, Coimbra, June 2014 4 « EMR, IBC and energy management of a Hybrid Locomotive» • starting 2004, • more than 750 researchers