An Energy Management Strategy of Hybrid Energy Storage ... slides_1.pdf · EVS28 KINTEX, Korea, May...
Transcript of An Energy Management Strategy of Hybrid Energy Storage ... slides_1.pdf · EVS28 KINTEX, Korea, May...
EVS28KINTEX, Korea, May 3-6, 2015
An Energy Management Strategy of
Hybrid Energy Storage Systems for
Electric Vehicles Electric Vehicles
Chunhua Zheng1, Zhongming Pan1, Guoqing Xu2 , SukWon Cha31Shenzhen Institutes of Advanced Technology CAS, 1068 Xueyuan Avenue, Shenzhen University Town,
Shenzhen, P.R.China, [email protected] Chinese University of Hong Kong
3Seoul National University
Contents
Introduction
The vehicle model
The proposed energy management strategy
2
The proposed energy management strategy
Conclusion
Introduction
I. Background
1. Currently, pure electric vehicles (PEVs) usually use the single energy
storage system (ESS), i.e. the battery;
2. Batteries have a limited power density due to their chemical
characteristics;characteristics;
3. Super-capacitors present good power density, however they are
difficult to provide a good performance on the energy density;
4. A hybrid energy storage system (HESS) which consists of a battery
and a super-capacitor shows an improved performance considering
both the power and energy densities compared to the single ESS case.
3
Introduction
II. Objectives
1. This paper proposes an energy management strategy of the HESS for
PEVs, which is based on the Minimum Principle;
2. The control objective of the energy management strategy is to
optimize the entire efficiency of the HESS and meanwhile to
prolonging the battery lifetime.
4
The vehicle model
I. Configuration of an EV with the HESS
1. The battery and the super-capacitor can recover the vehicle braking
energy;
2. The battery can also provide a part of energy to the super-capacitor in
some cases.
5
Battery
Super-capacitor
Motor Vehicle
The vehicle model
II. Battery model
1. The internal resistance model is used;
2. The open circuit voltage (OCV) and the internal resistance are
dependent on the battery state of charge (SOC).
Battery
Super-capacitor
Motor Vehicle
6
0 0.2 0.4 0.6 0.8 1310
320
330
340
350
360
Battery SOC
Bat
tery
OC
V (
V)
0 0.2 0.4 0.6 0.8 10.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
Battery SOC
Inte
rnal
res
ista
nce
(O
hm
)
Charging
Discharging
Vbat(SOCbat)
Rbat(SOCbat)Ibat
Pbat
2( ) ( ) 4 ( )1
2 ( )bat bat bat bat bat bat bat
bat
bat bat bat
V SOC V SOC R SOC PSOC
Q R SOC
•
⋅− − ⋅= −
The vehicle model
III. Super-capacitor model
1. A simple model is used for the super-capacitor;
2. The super-capacitor module data are described below.
Battery
Super-capacitor
Motor Vehicle
( )
7
( )2
,max ,max
,max
41
2
sup sup sup sup sup sup
sup
sup sup sup
SOC V SOC V R PSOC
V C R
• ⋅ ⋅⋅
⋅
− − ⋅= −
Vsup
RsupIsup
Psup
Csup (F) 165
Vsup,max (V) 48.6
Rsup(mΩ) 10
The vehicle model
IV. Motor and vehicle models
1. An efficiency may is used for the electric motor;
2. The vehicle data are described below.
Battery
Super-capacitor
Motor Vehicle
8
Vehicle total mass (kg) 1500
Final drive gear efficiency (%) 95
Tire radius (m) 0.29
Aerodynamic drag coefficient 0.37
Vehicle frontal area (m2) 2.59
Air density (kg/m3) 1.21
Rolling resistance coefficient 0.014Speed (rad/s)
To
rqu
e (N
m)
0 100 200 300 400 500
-500
-400
-300
-200
-100
0
100
200
300
400
500
86
88
90
92
94
96
98
The proposed energy management strategy
I. Problem formulation
State equations: (state variables: battery SOC and super-capacitor SOC)
( )( )sup sup
,
,
bat bat bat
bat
SOC F P SOC
SOC f P SOC
•
•
=
=
Performance measure to be minimized: (control variable: battery power)
( ) ( ) 0
2
0, ,
ft
bat bat bat bat bat batt
J P P SOC k I P SOC dt= + ⋅∫
The total power is known, thus the
battery power can be used here.
9
Hamiltonian
Necessary conditions for obtaining the optimal
solution:
0t∫
( ) ( ) ( ) ( )2
0 1 2 sup, , , ,
bat bat bat bat bat bat bat bat batH P P SOC k I P SOC p F P SOC p f P SOC= + ⋅ + ⋅ + ⋅
( ) ( )
* *
sup
1 2
* *
1 2
sup
* * * * * * * * *
sup 1 2 sup 1 2
; ;
; ;
, , , , , , , ,
bat
bat
bat bat bat bat
H HSOC SOC
p p
H Hp p
SOC SOC
SOC SOC P p p SOC SOC P p pH H
• •
• •
∂ ∂= =∂ ∂∂ ∂= − = −
∂ ∂
≤
Battery energy term Battery lifetime term
The proposed energy management strategy
II. Simulation results of the proposed strategy1. Two examples of the Hamiltonian are illustrated below, which are calculated at
60s and 500s of the Japan1015 driving cycle respectively;
2. The third term of the Hamiltonian is neglected here, given that it overlaps with
the first term.
-100 -80 -60 -40 -20 0 20 40 60 80 100-2
0
2x 10
5
H1
-100 -80 -60 -40 -20 0 20 40 60 80 100-2
0
2x 10
5
H1
10
-100 -80 -60 -40 -20 0 20 40 60 80 1000
5
10x 10
5
H2
-100 -80 -60 -40 -20 0 20 40 60 80 100-2
0
2x 10
5
H4
-100 -80 -60 -40 -20 0 20 40 60 80 1000
5
10x 10
5
H
Battery power
-100 -80 -60 -40 -20 0 20 40 60 80 1000
5
10x 10
5
H2
-100 -80 -60 -40 -20 0 20 40 60 80 100-2
0
2x 10
5
H4
-100 -80 -60 -40 -20 0 20 40 60 80 1000
5
10x 10
5
H
Battery power
The proposed energy management strategy
II. Simulation results of the proposed strategy
1. Japan1015 driving cycle is used to the simulation;
2. The results are obtained by considering both the HESS efficiency and
the battery lifetime;
3. The battery power for the entire driving cycle does not change too
much, this is beneficial to the battery lifetime.
11
0 100 200 300 400 500 600 700-15
-10
-5
0
5
10
15
20
time (s)
Po
wer
(k
W)
Battery power
Super-capacitor power
0 100 200 300 400 500 600 7000
20
40
60
80
Veh
icle
sp
eed
(k
m/h
)
0 100 200 300 400 500 600 700-10
0
10
20
30
To
tal
po
wer
(kW
)
time (s)
Conclusion & discussion
1. The proposed energy management strategy considers both the HESS
efficiency and battery lifetime;
2. The battery power does not change too much during entire driving,
this is beneficial to the battery lifetime;this is beneficial to the battery lifetime;
3. The proposed strategy needs to be further improved considering the
tradeoff between the battery energy saving and battery lifetime.
12
Thank you!
13