Syed Ahmed Corning - Illinois Institute of...

Power Coordination Control for a Hybrid Fuel Cell Vehicle using

Model Predictive Control

Syed Ahmed Corning

Oluwasanmi Adeodu

and Donald J. Chmielewski Illinois Institute of Technology

Department of Chemical and Biological EngineeringDepartment of Chemical and Biological Engineering

Illinois Institute of TechnologyIllinois Institute of Technology

Outline

• Motivation and Background

• Profit Control

• Controller Embedded System Design:

- Hybrid Vehicle Equipment Sizing

• Smart Grid



Hybrid Vehicle Equipment

iscap

Rscap

Escap

iarm

Rarm

Larm

ibat

Rbat

Ebat

ifc

EfcFuel

Cell

Power Bus

warm

Earm



Hybrid Vehicle Operation

iascap

iscap

Rscap

Escap

iarm

Rarm

LarmDC-DC

Converter

iabatibat

Rbat

Ebat

DC-DC

Converter

iafcifc

EfcDC-DC

Converter

Fuel

Cell

Power Bus

warm

Earm

kfc kbat kscap



Servo-Loops with PI Controllers

Vehicle

Power

System

+ -Pscap

(sp) Pscap

kscap

+ -Pbat

(sp) Pbat

kbat

+ -Pfc

(sp) Pfc

kfc

PI

PI

PI



Supervisory Control

Vehicle

Power

System

+ -Pscap

(sp) Pscap

kscap

High

Level

Controller

Pmot(sp)

+ -Pbat

(sp) Pbat

kbat

+ -Pfc

(sp) Pfc

kfc

PI

PI

PI



High Level Battery Model

)(loss

batbatbat PPE

max0 batbat EE

maxmin

batbatbat PPP

2

,

)(

batbatl

loss

bat PcP



High Level Super Capacitor Model

)(loss

scscsc PPE

max0 scsc EE

maxmin

scscsc PPP

2

,

)(

scscl

loss

sc PcP



High Level Fuel Cell Model

fcfc PP

max0 fcfc PP

maxmin

fcfcfc PPP



Driver Commands

Vehicle

Power

System

+ -Pscap

(sp) Pscap

kscap

High

Level

Controller

Pmot(sp)

+ -Pbat

(sp) Pbat

kbat

+ -Pfc

(sp) Pfc

kfc

PI

PI

PI

fcscbatmot PPPP

Power Balance:

2

, scsclscsc PcPE

fcbatmotsc PPPP



Constraints Motivate the use of MPC

Ebat

Pbat

Esc

Psc

Pfc

ΔPfc

max0 batbat EE

maxmin

batbatbat PPP

max0 scsc EE

maxmin

scscsc PPP

max0 fcfc PP maxmin

fcfcfc PPP




Vehicle

Power

System

+ -Pscap(sp) Pscap

kscap

MPC

Pmot(sp)

+ -Pbat(sp) Pbat

kbat

+ -Pfc(sp) Pfc

kfc

PI

PI

PI




iii

ik

ikuikxik

ikikik

Ni

ik

ik

T

ikik

T

ikux

xx

zzz

uDxDz

BuAxx

tsuRuxQxikik

|

max

|

min

|||

|||1

1

||||,

..)(min||



Economic Linear Optimal Control

Steady-State

Operating

Line

Steady-State

Operating

Line

Optimal Steady-State

Operating Point

Expected

Dynamic

Operating

Region

Steady-State

Operating

Line


Operating Point

Minimally

Baked-off

Operating

Point

Expected

Dynamic

Operating

Regions

Steady-State

Operating

Line


Operating Point

Different Controller

Tuning Values

Expected

Dynamic

Operating

Regions

Steady-State

Operating

Line


Operating Point

Minimally

Baked-off

Operating

Point

Different Controller

Tuning Values

Expected

Dynamic

Operating

Regions

Steady-State

Operating

Line


Operating Point

iELOCi xLu



Where are the Economics?

2

,

)(

batbatl

loss

bat PcP 22

,

)()(

batbatbatl

loss

bat

loss

bat

Pc

PPE

)(loss

batbatbat PPE )(0 loss

batbat PP

22

,

)( 0 batbatbatlbatbat

loss

bat PcPPP



Time-Series Plots (decomposition of time scales)

0 0.5 1-20

-10

0

10

20

Pbat

hours

0 0.5 1

-20

-10

0

10

20

Psc

hours

0 0.5 11.7

1.8

1.9

2x 10

4

Ebat

0 0.5 10

50

100

150

200

Esc

0 0.5 1

0

0.2

0.4

0.6

Pfc

0 0.5 1-20

-10

0

10

20

dP

fc

hours



Acknowledgements

• Current Students and Former Students: Ben Omell David Mendoza-Serrano

Dr. Ming-Wei Yang (Taiwan Electric) Dr. Jui-Kun Peng (ANL)

Amit Manthanwar • Funding: National Science Foundation (CBET – 0967906) Starr Research Fellowship Graduate and Armour Colleges, IIT Department of Chemical & Biological Engineering, IIT



Conclusions

• Relationship between control system performance

and plant profit quantified.

• Profit guided controller design.

• Allows for controller embedded system design

• Broad set of applications from a variety of

disciplines.

• Non-convex, but global methods can be used to

size and/or select equipment.

Syed Ahmed Corning - Illinois Institute of...

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