Parameter design of regenerative braking strategy and ... slides... · Parameter design of...
Transcript of Parameter design of regenerative braking strategy and ... slides... · Parameter design of...
EVS28 KINTEX, Korea, May 3-6, 2015
Parameter design of regenerative
braking strategy and battery range of
use of electric vehicle using the
Optimization Technique
Kiyoung Kim1, Seungwan Son1 , Sukwon Cha1 1School of Mechanical & Aerospace Engineering, Seoul National
University, Gwanak-ro 1, Gwanak-gu Seoul 151-744, Republic of Korea,
Introduction
I. Target electric vehicle
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Mortor Inverter
Battery
forward direction
Mechanical connection Electrical connection
Component Value
Vehicle weight 1260kg
Radius of tire 0.35m
Reduction ratio 3.6
Motor 50kW
Battery capacity 16.4kWh
Rear drive Compact car
Target vehicle
Optimization Technique
I. Optimal parameter using Taguchi method
1. Statistical method developed by Genichi Taguchi
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• Optimization using steepest gradient method
known J= J(x1, …., xn)
• Optimization using Taguchi method
unknown SN= SN(x1, …., xn)
SN: signal-to-noise ratio
Objective and function parameter
I. Objective
1. Maximization of efficiency of electric vehicle regardless of various
using condition
II. Function parameter
1. efficiency of electric vehicle (km/kWh)
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max y =𝑦1
𝑦1,𝑟𝑒𝑓
𝑦1
𝑦1,𝑟𝑒𝑓
: efficiency
: efficiency reference
Forward simulator
I. Analysis of efficiency by simulation program based on
MATLAB/Simulink
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Forward simulation program considering power train dynamics Simulation using component data map Determine traction power comparing vehicle speed with target speed
Design parameter
I. Initial SOC
II. SOC range of use
III. Ratio of front/rear hydraulic pressure based on vehicle
deceleration
Parameter combination in correlation
• Initial SOC & SOC range of use
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Design parameter
I. Initial SOC
1. Different OCV and internal resistance for SOC
→ Different battery efficiency for SOC
→ To find optimal initial SOC
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※SOC : State of Charge
=current charge amount
Maximum charge amount
Design parameter
II. SOC range of use
1. Different OCV and internal resistance for SOC
→ Different battery efficiency for SOC
→ To find optimal range of use
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※SOC : State of Charge
=current charge amount
Maximum charge amount
Design parameter
I. Ratio of front/rear hydraulic pressure based on vehicle
deceleration
1. Total brake force = regenerative brake(motor) + mechanical brake(hybraulic)
2. Ideal brake distribution rate based on vehicle deceleration(blue line)
3. Real brake distribution rate only by mechanical brake (red line)
4. Regenerative braking makes up for deficient rear braking force
5. Meeting point ideal/real line as design parameter (green point)
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Rear b
rake fo
rce(N
)
Front brake force(N)
0.2g
0.4g
0.6g 0.8g
Ideal brake force distribution
Real brake force distribution
Rear b
rake fo
rce(N
)
Front brake force(N)
0.2g
0.4g
0.6g 0.8g
Ideal brake force distribution
Real brake force distribution
Product using condition
I. Driving propensity of driver
1. Indexing based on Aggressiveness factor
2. Aggressiveness factor?
1) Based on required traction power
2) Effect on efficiency according to driving pattern
can be quantified
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𝐴𝑔𝑔 = 𝑎 · 𝑣 +𝑑𝑡
𝑣𝑑𝑡
<Fuel economy of conventional car for aggresiveness> <various driving cycle>
Level of design parameter and using condition
I. Level of design parameter on primary
II. Level of using condition on primary
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Design parameter Description on design parameter Level 1 Level 2 Level 3
A Initial SOC(0~1) 0.75 0.95 -
B SOC range of use(0~1) 0.55 0.60 0.65
C Meeting point ideal/real line 0.4g 0.6g 0.8g
Using condition Level 1 [𝑁1] mildest
Level2 [𝑁𝟐] harshest
aggressiveness 0.0697
(HWFET cycle) 0.1646
(UDDS cycle)
Result of primary process
I. 𝐿18(21ⅹ32) Array
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Combination
Design parameter Using condition
Function parameter
S/N ratio
I. Table and graph of S/N ratio for level of design parameter
Analysis on sensitivity
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Level
Max. difference
S/N
ratio
S/N
ratio
S/N
ratio Level of B
Level of A
Level of C
Design parameter A does not influence on function parameter due to low sesitivity
Design parameter B and C influence on function parameter due to high sesitivity
Analysis on parameter correlation
I. Table and graph of Correlation A with B
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slope of design parameter A&B for level is similar
→ Low correlation between A and B
Estimation of S/N ratio
I. Estimation of S/N ratio and comparison with result
1. Design parameter B&C influence on S/N ratio
2. Design parameter A and A-B do not influence on S/N ratio
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Combination
Design parameter Using condition
Function parameter
S/N ratio
Level2 of A is selected because S/N ratio is lager than that of level 1 of A
Level of design parameter and using condition
I. Level of design parameter on second
II. Level of using condition on second
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Design parameter Description on design parameter Level 1 Level 2 Level 3
A Initial SOC(0~1) - 0.95 -
B SOC range of use(0~1) 0.65 0.70 0.75
C Meeting point ideal/real line 0.8g 0.85g 0.9g
Using condition Level 1 [𝑁1] mildest
Level2 [𝑁𝟐] harshest
aggressiveness 0.0697
(HWFET cycle) 0.1646
(UDDS cycle)
Result of second process
I. 𝐿9(32) Array
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Combination
Design parameter Using condition
Function parameter
S/N ratio
I. Table and graph of S/N ratio for level of design parameter
Analysis on sensitivity
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Level
Max. difference
S/N
ratio
S/N
ratio
Level of B Level of C
Design parameter B&C do not influence on function parameter
No need to third process
B C
Estimation of S/N ratio
I. Estimation of S/N ratio and comparison with result
1. Design parameter B&C do not influence on S/N ratio
2. Combination number 6 is optimal combination
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S/N ratio more bigger than primary process
Combination
Design parameter Using condition
Function parameter
S/N ratio
Conclusion
I. Determine Optimal parameter of EV using Taguchi method
II. Design parameter 1. Initial SOC
2. SOC range of use
3. Ratio of front/rear hydraulic pressure based on vehicle deceleration
III. Product using condition 1. Aggressiveness factor
IV. Optimal design parameter combination
1. Select parameter combination making S/N ratio maximized
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Design parameter Description on design parameter Optimum
A Initial SOC(0~1) 0.95
B SOC range of use(0~1) 0.7
C Meeting point ideal/real line 0.9g
Acknowledgement & Reference
This work was supported by the Hyundai Motor Company and the National Research
Foundation of Korea(NRF) grant funded by the Ministry of Science, ICT &
Future Planning (MSIP) (No. 2009-0083495).
• Daeheung Lee et. Al., “System Efficiency Analysis for Next Generation Eco-Friendly
Vehicles with Aggressiveness of Real-World Driving Schedules” , Transactions of KSAE,
2010.11, pp. 3178-3183
• Mehrdad Ehsani et. Al., “Modern Electric, Hybrid Electric, and Fuel Cell Vehicles”, 2nd
edition, CRC Press, 2010
• 김종원, “공학설계 : 창의적 신제품 개발방법론”, 서울 : 문운당, 2008
• Ho Gi Kim, “Suppression Control of the Drivetrain-Oscillations of an Electric Vehicle using
Taguchi method.”, Transaction of KSME, 2009. 5 Vol.33 No.5 pp.463-468
• Chunhua Zheng, “ A study on Battery SOC Estimation by Regenerative Braking in Electric
Vehicle” Transaction of KSAE, Vol. 20 No. 1, pp.119-123
• Yongsun Bak, “Development of regenerative braking co operative control algorithm for
electric vehicle equipped with booster brake” Transactions of KSAE, 2013.5, pp. 1800-1804
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