In this study we present a procedure for the design and implementation of a control strategy to optimize energy use within a light weight hydraulic hybrid passenger vehicle. The hydraulic hybrid utilizes a high pressure accumulator for energy storage which has superior power density than conventional battery technology. This makes fluid power attractive for urban driving applications in which there are frequent starts and stops and large startup power demands. A dynamic model of a series hydraulic hybrid powertrain is presented along with the design of a model predictive control based energy management strategy. Model predictive control was chosen for this study because it uses no future information about the drive cycle in its design. This increases the flexibility of the controller allowing it to be directly applied to a variety of drive cycles. Using the model predictive framework, a holistic view of the powertrain was taken in the design of the control strategy, and the impact of each actuator’s efficiency on overall efficiency was evaluated. A hardware-in-the-loop experiment using an electro-hydraulic powertrain testbed was then used to validate the dynamic model and control performance. Through a simulation study in which each actuator’s efficiency was given varying levels of priority in the objective function, it was found that overall system efficiency could be improved by allowing for small sacrifices in individual component performance. In fact, the conventional wisdom of using the additional degrees of freedom within a hybrid powertrain to optimize engine efficiency was found to yield the lowest overall powertrain efficiency. In this work we present a rigorous framework for the design of an energy management strategy. The design method improves the powertrain’s operational efficiency by finding the best balance between optimizing individual component efficiencies. Furthermore, since the design of the control strategy is built upon an analysis of individual components, it can be readily extended to other architectures employing different actuators.

References

References
1.
Department of Energy, 2009, “
Annual Energy Review 2009
,”
Energy Information Administration (EIA)
.
2.
www.whitehouse.gov/sites/default/files/fuel_economy_report.pdf.
3.
Burke
,
A.
, 2007, “
Batteries and Ultracapacitors for Electric, Hybrid and Fuel Cell Vehicles
,”
Proc. IEEE
,
95
(
4
), pp.
806
820
.
4.
Lam
,
L. T.
, and
Louey
,
R.
, 2006, “
Development of Ultra-Battery for Hybrid-Electric Vehicle Applications
,”
J. Power Sources
,
158
(
2
), pp.
1140
1148
.
5.
Diego-Ayala
,
U.
,
Martinez-Gonzalez
,
P.
,
McGlashan
,
N.
, and
Pullen
,
K. R.
, 2008, “
The Mechanical Hybrid Vehicle: An Investigation of a Flywheel-Based Vehicular Regenerative Energy Capture System
,”
Proc. Inst. Mech. Eng. Part D (J. Automob. Eng.)
222
(
11
), pp.
2087
2101
.
6.
Van de Ven
,
J. D.
,
Olson
,
M. W.
, and
Li
,
P. Y.
, 2008, “
Development of a Hydro-Mechanical Hydraulic Hybrid Drive Train With Independent Wheel Torque Control for an Urban Passenger Vehicle
,” International Fluid Power Exposition.
7.
Filipi
,
Z.
, and
Kim
,
Y. J.
, 2010, “
Hydraulic Hybrid Propulsion for Heavy Vehicles: Combining the Simulation and Engine-In-the-Loop Techniques to Maximize the Fuel Economy and Emission Benefits
,”
Oil Gas Sci. Technol.
,
65
(
1
), pp.
155
178
.
8.
Hui
,
S.
, and
Junqing
,
J.
, 2010, “
Research on the System Configuration and Energy Control Strategy for Parallel Hydraulic Hybrid Loader
,”
Autom. Constr.
,
19
, pp.
213
220
.
9.
Wu
,
B.
,
Lin
,
C. C.
,
Filipi
,
Z.
,
Peng
,
H.
, and
Assanis
,
D.
, 2004, “
Optimal Power Management for a Hydraulic Hybrid Delivery Truck
,”
Veh. Syst. Dyn.
,
42
(
1–2
), pp.
23
40
.
10.
Johri
,
R.
, and
Filipi
,
Z.
, 2009, “
Low-Cost Pathway to Ultra Efficient City Car: Series Hydraulic Hybrid System With Optimized Supervisory Control
,”
SAE Int. J. Engines
,
2
(
2
), pp.
505
520
.
11.
Stelson
,
K. A.
, and
Meyer
,
J. J.
, 2008, “
Optimization of a Passenger Hydraulic Hybrid Vehicle to Improve Fuel Economy
,”
7th JFPS International Symposium on Fluid Power
.
12.
Deppen
,
T. O.
,
Alleyne
,
A. G.
,
Stelson
,
K. A.
, and
Meyer
,
J. J.
, 2011, “
A Model Predictive Control Approach for a Parallel Hydraulic Hybrid Powertrain
,”
Proceedings of the American Control Conference
.
13.
Backe
,
W.
, 1993, “
Present and Future of Fluid Power
,”
Proc. Inst. Mech. Eng., Part I (J. Syst. Control Eng.)
,
207
(
4
), pp.
193
212
.
14.
Mcauley
,
J. W.
, 2003, “
Global Sustainability and Key Needs in Future Automotive Design
,”
Environ. Sci. Technol.
,
37
(
23
), pp.
5414
5416
.
15.
Filipi
,
Z.
,
Louca
,
L.
,
Daran
,
B.
,
Lin
,
C. C.
,
Yildir
,
U.
,
Wu
,
B.
,
Kokkolaras
,
M.
,
Assanis
,
D.
,
Peng
,
H.
,
Papalambros
,
P.
,
Stein
,
J.
,
Szkubiel
,
D.
, and
Chapp
,
R.
, 2004, “
Combined Optimisation of Design and Power Management of the Hydraulic Hybrid Propulsion System for the 6 × 6 Medium Truck
,”
Int. J. Heavy Veh. Syst.
,
11
(
3–4
), pp.
372
402
.
16.
Meyer
,
J. J.
,
Stelson
,
K. A.
,
Alleyne
,
A. G.
, and
Deppen
,
T. O.
, 2010, “
Power Management Strategy for a Parallel Hydraulic Hybrid Passenger Vehicle Using Stochastic Dynamic Programming
,”
Proceedings of 7th International Fluid Power Conference
.
17.
Deppen
,
T. O.
,
Alleyne
,
A. G.
,
Stelson
,
K. A.
, and
Meyer
,
J. J.
, 2010, “
Predictive Energy Management for Parallel Hydraulic Hybrid Passenger Vehicle
,”
Proceedings of the ASME Dynamic Systems and Control Conference
.
18.
Zhang
,
R.
,
Alleyne
,
A. G.
, and
Prasetiawan
,
E.
, 2002, “
Modeling and H2/H∞ MIMO Control of an Earthmoving Vehicle Powertrain
,”
ASME J. Dyn. Syst., Meas., Control
,
124
, pp.
625
636
.
19.
Montgomery
,
A. J.
, and
Alleyne
,
A. G.
, 2006, “
Optimizing the Efficiency of Electro-Hydraulic Power Trains
,”
Proceedings of International Mechanical Engineering Congress and Exposition
.
20.
Prasetiawan
,
E. A.
,
Zhang
,
R.
,
Alleyne
,
A. G.
, and
Tsao
,
T. C.
, 1999, “
Modeling and Control Design of a Powertrain Simulation Testbed for Earthmoving Vehicles
,” International Mechanical Engineering Congress and Exposition: The Fluid Power and Systems Technology Division.
21.
Zhang
,
R.
, and
Alleyne
,
A.
, 2005, “
Dynamic Emulation Using an Indirect control Input
,”
ASME J. Dyn. Syst., Meas., Control
,
127
, pp.
114
124
.
22.
Carter
,
D. E.
, 2003, “
Load Modeling and Emulation for an Earthmoving Vehicle Powertrain
,” M.S. thesis in Mechanical and Industrial Engineering, University of Illinois, Urbana-Champaign.
23.
Takasaki
,
A.
,
Mizutani
,
T.
,
Kitagawa
,
K.
,
Yamahana
,
T.
,
Odaka
,
K.
,
Kuzuya
,
T.
,
Mizuno
,
Y.
, and
Nishikawa
,
Y.
, 2009, “
Development of New Hybrid Transmission for 2009 Prius
,”
Proceedings of the EVS24 International Battery, Hybrid Fuel Cell Electric Vehicle Symposium
.
24.
Maciejowski
,
J. M.
, 2002,
Predictive Control With Constraints
,
Prentice-Hall
,
Englewood Cliffs, NJ.
25.
Boyd
,
S.
, and
Vandenberghe
,
L.
, 2009,
Convex Optimization
,
Cambridge University Press
,
New York
.
You do not currently have access to this content.