07 Guezennec FC Workshop OSU YG
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Transcript of 07 Guezennec FC Workshop OSU YG
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8/2/2019 07 Guezennec FC Workshop OSU YG
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Supervisory Control of Fuel Cell
Vehicles
Fuel Cell Control Workshop Irvine, CA
April 3 & 4, 2003
Yann Guezennec, Giorgio Rizzoni and Gabriel Choi
Ohio State University
Center for Automotive Research
http://car.eng.ohio-state.edu
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Focus on Fuel Cell Systems for automotive applications, more
particularly PEM
Emphasis on complete systems rather than in-depth component
analysis
Treat the electro-chemistry as a black box Two levels of modeling:
Quasi-static approach, i.e., steady-state characteristics +
slow thermal dynamics (suitable for energy analysis at the
system level and vehicle level, system optimization and
supervisory control strategy) Low-frequency dynamics approach, i.e., particularly the air
supply dynamics under varying loads as seen in automotive
powertrains (suitable for low-level system control)
Strong interplay between both levels
Overview of our PEM FC
Modeling Approach (contd)
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Imbedded levels of modeling:
Stack: Computationally efficient, yet accurate black-box
fuel cell stack model environment as a function of relevant
operating and control parameters implemented in a
Matlab/Simulink
System: Fuel cell system (stack and necessary auxiliaries)
model implemented in Matlab/Simulink Vehicle: Fuel cell system model implemented within our
modular, scalable vehicle performance simulator (VP-SIM)
Overview of our PEM FCModeling Approach (contd)
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Fuel Cell System Model Integrated into VP-SIM, aForward Vehicle Performance Simulator
P o we r t ra i n L a y e r
1
Tract ive Force (N)
Ft_ f
F t _ r
F t
W h e e l
C o u p l i n g
alp
ha
beta
em_
ctrl
fc_
trl
c_
gear
c_
brakeVC U
Te rmin a t o r5
Te rm in a t o r4
Te rm in a t o r3
T
w
F t
v
R e a r
Whee ls1
c _ b r a k e _ r
T_i
w_ i
T_ o
w_ o
R e a r
B ra k e s
e m _ c d e
V_ba t t
i_batt
p _ f c
V _ f c
i _ f c
V_ o
i_o
P o we r A mp f c
H V _ H 2
m f _ H 2
V
I
P E M_ Fu e l_ c e l l _ s y s t e m
H v
m f
H y d r o g e n T a n k
G ro u n d
T
w
F t
v
Fro n t
Whee ls1
c _ b r a k e _ f
T_ i
w_ i
T_ o
w_ o
Front
B ra k e s
V
i
T
w
E M 1
T_i
w_ i
T_ o
w_ o
Di f f e re n t i a l 1
V
i
B a t t e ry
2B ra k e A n g le
(0 to 1 )1A c c e l A n g le
(0 to 1)
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PEM Fuel Cell Vehicles: a Need for
Hybridization ?
Hybridization (i.e., batteries, supercapacitors) isprobably needed for:
Fuel cell sizing optimization Cold start and dynamic response
Energy efficiency improvement (regen + shift inoperating conditions)
Lesser needs for low-level control and dynamic
response
Hybridization creates the need for vehicle-level,energy management (supervisory) control strategy
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Fuel Cell Hybridization
The directionality of the electrical energy flow must be controlled in
hybrid fuel cell vehicle (similar to power split management problem
in ICE/EM parallel hybrids)
Need for power electronics to couple fuel cell system and
batteries/supercaps due to differences in voltage/current characteristiccurves
+++
Fuel
Cell
System---
+ +
Power
Converter
DC/DC
- -
+++
Battery
---
Electric
Motor
+
Power
Converter
DC/AC
-
++++High Voltage DC Bus ++++
-----High Voltage DC Bus -----
Fuel Cell Power
Control input
Electric Motor Power
Control input
IFC
Power flow from
fuel cell to DC high
voltage battery bus
Power flow between DC high
voltage battery bus and electric motor
(positive in traction, negative in
regenerative braking)
IBatt
+++
Fuel
Cell
System---
+ +
Power
Converter
DC/DC
- -
+++
Battery
---
Electric
Motor
+
Power
Converter
DC/AC
-
++++High Voltage DC Bus ++++
-----High Voltage DC Bus -----
Fuel Cell Power
Control input
Electric Motor Power
Control input
IFC
Power flow from
fuel cell to DC high
voltage battery bus
Power flow between DC high
voltage battery bus and electric motor
(positive in traction, negative in
regenerative braking)
IBatt
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Aim of Supervisory Control Strategy
(Energy Management)
To define
Real time power distribution between FC and the
electrical accumulator (Pfc: control variable)
which:
Satisfy instantaneous driver power demand (Pem)
Minimize overall fuel consumption (global)
with respect to:
Components limits
Charge-sustaining constraints (global)
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ECMS Control Strategy Highlights
Initially developed for parallel HEV
Applicable to any hybrid configuration Reducing the non-realizable global minimization
criterion to a realizable local one (causal)
Based on the concept of an equivalent fuel consumption
for the electrical accumulator
Computationally cheap for real-time implementation
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Concept of Equivalent Fuel Consumption
Charge sustaining => All energy depleted from electricalaccumulator has to be replaced
An average Virtual accumulator specific fuel consumptionSC (gr/kW.hr) can be calculated:Fuel Tank Electrical
Accumulator
FuelCell
fcfm _&
Pbatt
Power
Converter
Pfc
Fuel Tank Electrical
Accumulator
FuelCell
fcfm _&
Pbatt
Power
Converter
Pfc
battfbatt mE _battSC
_batt f batt P m &
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ECMS Principles At each time:
Each candidate power combination is examined, combinations which dontmeet driver request are rejected
The instantaneous minimization of the equivalent fuel consumption does not
lead to a charge-sustaining strategy
To enforce the global SOC constraint, the equivalent fuel consumption isfurther modified by using an appropriately constructed multiplicative penaltyfunction to bias the optimal instantaneous split towards or away from theuse of the electrical accumulator (i.e., increase or decrease the equivalent
fuel consumption for the electric accumulator
( ) ( ) ( )fc bat t emP i P i P i+ =
( ) ( ) ( )_ _ _f fc f ba t t f e qu im i m i m i+ =& & &
Fuel CellModel
b a t t penS C f
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SOC Control via Multiplicative Penalty
Function on Equivalent Fuel Consumption
Penalty function on electrical consumption should reflect not only theinstantaneous deviation from target SOC, but also the accumulateddeviation (PI-like controller). However, the integral term must be weakenough to allow enough flexibility, i.e., instantaneous and short-termdeviations from target SOC are required to best utilized the hybridizationpotential
Weak
integral
term
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ECMS Supervisory Control Strategy ECMS Advantages:
Implementable (causal): requires only present and pastinformation
Computationally cheap: past information is only accumulatedsum real time implementation
Proven in simulation and in the field
Implications of ECMS control strategy w.r.t. dynamicrequirements on fuel cell system, drivability, etc. What are the implications with respect to fuel cell system dynamic
response?
If limiting rate of change of fuel cell system power (downgrading ofoptimal split) is implemented, how sub-optimal is it?
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Representative Simulation Results for
Charge-Sustaining FC/Battery Vehicle
Simulation Parameters:
FCV sedan-like (Mv = 1700 Kg,
Cd = 0.35, Af= 1.8 m2)Drive cycle = FUDS (Hot Start,
T = 80C)
50 kW Fuel Cell System
(nominal)
Fuel cell system architecture and
control: pressurized with screw
compressor, optimal systemefficiency tracking
+/- 30 kW Battery Max Power
SOC Target = 0.4 - 0.8
Initial SOC = 0.6
Battery capacity = 4.4 A.h
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Case 1 No hybridization
Power
split
SOC
Power
histogram
and
efficiency
Fuel
consumption
MH2 = 157.0 gr
High dynamics
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Case 2 Hybridized, Optimal Power Split
Power
split
SOC
Power
histogram
and
efficiency
Fuel
consumption
MH2 = 105.9 gr
Decreased dynamics
Charge sustaining
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Details of ECMS Supervisory Control
Strategy Output
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Case 3 Hybridized, Optimal Split, Slew
Rate Limited to 2 kW/sec
Power
split
SOC
Power
histogram
and
efficiency
Fuel
consumption
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Details of ECMS Supervisory Control Strategy
Output with Rate Limitation of 2 kW/sec
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Summary Results
5.2382.91105.565.0
5.1183.59104.704.5
5.1283.58104.724.0
5.1283.41104.933.5
5.1583.22105.163.0
5.1583.42104.922.5
5.1683.18105.222.0
6.1976.98113.701.5
6.0375.99115.181.0
10.3354.70160.000.5
HEV-2
5.2982.68105.86HEV-1
8.4255.76156.97HEV-0
Standard Deviation of the
FC Power[kW]
Equivalent Mileage
[mile/gallon]
Hydrogen Consumption
[gram]
Rate Limit
[kW/sec]Hybrid Type
Effect of the Hybrid Types and Control Strategies with Screw-Type Compressor
ran with the best system-efficiency operating condition
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Summary Results
Effect of the Control Strategies with Screw-Type Compressor
ran with the best system-efficiency operating condition
Hybridization with ECMSSupervisory Control Strategy
can tolerate poor dynamic
response of fuel cell system
with no fuel economy
degradation