Abstract

This paper presents the exploration and optimization of a hybridized opposed piston (OP) engine. In this work, the exhaust crankshaft lead (ECL) is introduced as a controllable parameter in the hybridized OP engine enabled by eliminating the conventional geartrain linking the two crankshafts of an OP engine. This allows for variation in the effective compression and expansion ratio of the engine, along with scavenging performance. This novel control actuator as well as the adjustable speed and load setpoint in a series hybrid OP engine powertrain architecture necessitates an intensive calibration effort to realize any possible efficiency improvements. However, the OP engine within this series hybrid powertrain does not need to operate in highly transient conditions, but rather its operating point is fixed or slowly varying. This property permits the use of online calibration techniques. After manually sweeping speed and ECL values at two power setpoints, the use of an extremum-seeking type intercycle optimization algorithm to optimize the operating setpoint is validated, showing that near optimal speed and ECL setpoints can be selected despite the relatively flat operating map of the OP engine.

References

1.
Hannan
,
M.
,
Azidin
,
F.
, and
Mohamed
,
A.
,
2014
, “
Hybrid Electric Vehicles and Their Challenges: A Review
,”
Renew. Sust. Energy Rev.
,
29
, pp.
135
150
.10.1016/j.rser.2013.08.097
2.
Enang
,
W.
, and
Bannister
,
C.
,
2017
, “
Modelling and Control of Hybrid Electric Vehicles (a Comprehensive Review)
,”
Renew. Sust. Energy Rev.
,
74
, pp.
1210
1239
.10.1016/j.rser.2017.01.075
3.
Tran
,
M.-K.
,
Bhatti
,
A.
,
Vrolyk
,
R.
,
Wong
,
D.
,
Panchal
,
S.
,
Fowler
,
M.
, and
Fraser
,
R.
,
2021
, “
A Review of Range Extenders in Battery Electric Vehicles: Current Progress and Future Perspectives
,”
World Electric Veh. J.
,
12
(
2
), p.
54
.10.3390/wevj12020054
4.
Regner
,
G.
,
Johnson
,
D.
,
Koszewnik
,
J.
,
Dion
,
E.
,
Redon
,
F.
, and
Fromm
,
L.
,
2013
, “
Modernizing the Opposed Piston, Two Stroke Engine for Clean, Efficient Transportation
,”
SAE
Paper No. 2013-26-0114.10.4271/2013-26-0114
5.
Drallmeier
,
J. A.
,
Hofmann
,
H.
,
Middleton
,
R.
,
Siegel
,
J.
,
Stefanopoulou
,
A.
, and
Salvi
,
A.
,
2021
, “
Work Extraction Efficiency in a Series Hybrid Opposed Piston Engine
,”
SAE
Paper No. 2021-01-1242.10.4271/2021-01-1242
6.
Drallmeier
,
J.
,
Siegel
,
J. B.
,
Middleton
,
R.
,
Stefanopoulou
,
A. G.
,
Salvi
,
A.
, and
Huo
,
M.
,
2021
, “
Modeling and Control of a Hybrid Opposed Piston Engine
,”
ASME
Paper No. ICEF2021-67541.10.1115/ICEF2021-67541
7.
Yu
,
X.
,
Zhu
,
L.
,
Wang
,
Y.
,
Filev
,
D.
, and
Yao
,
X.
,
2022
, “
Internal Combustion Engine Calibration Using Optimization Algorithms
,”
Appl. Energy
,
305
, p.
117894
.10.1016/j.apenergy.2021.117894
8.
Roepke
,
K.
,
2014
, “
Design of Experiments for Engine Calibration
,”
J. Soc. Instrum. Control Eng.
,
53
(
4
), pp.
322
327
.10.11499/sicejl.53.322
9.
Popovic
,
D.
,
Jankovic
,
M.
,
Magner
,
S.
, and
Teel
,
A.
,
2006
, “
Extremum Seeking Methods for Optimization of Variable Cam Timing Engine Operation
,”
IEEE Trans. Control Syst. Technol.
,
14
(
3
), pp.
398
407
.10.1109/TCST.2005.863660
10.
Salek
,
F.
,
Babaie
,
M.
,
Hosseini
,
S. V.
, and
Bég
,
O. A.
,
2021
, “
Multi-Objective Optimization of the Engine Performance and Emissions for a Hydrogen/Gasoline Dual-Fuel Engine Equipped With the Port Water Injection System
,”
Int. J. Hydrogen Energy
,
46
(
17
), pp.
10535
10547
.10.1016/j.ijhydene.2020.12.139
11.
Atkinson
,
C.
, and
Mott
,
G.
,
2005
, “
Dynamic Model-Based Calibration Optimization: An Introduction and Application to Diesel Engines
,”
SAE
Paper No. 2005-01-0026.10.4271/2005-01-0026
12.
Bellis
,
V. D.
,
2016
, “
Performance Optimization of a Spark-Ignition Turbocharged VVA Engine Under Knock Limited Operation
,”
Appl. Energy
,
164
, pp.
162
174
.10.1016/j.apenergy.2015.11.097
13.
Zhao
,
J.
, and
Xu
,
M.
,
2013
, “
Fuel Economy Optimization of an Atkinson Cycle Engine Using Genetic Algorithm
,”
Appl. Energy
,
105
, pp.
335
348
.10.1016/j.apenergy.2012.12.061
14.
Samadani
,
E.
,
Shamekhi
,
A. H.
,
Behroozi
,
M. H.
, and
Chini
,
R.
,
2009
, “
A Method for Pre-Calibration of di Diesel Engine Emissions and Performance Using Neural Network and Multi-Objective Genetic Algorithm
,”
Iranian J. Chem. Chem. Eng.
,
28
, pp.
61
70
.10.30492/IJCCE.2009.6828
15.
Gutjahr
,
T.
,
Kruse
,
T.
, and
Huber
,
T.
,
2017
, “
Advanced Modeling and Optimization for Virtual Calibration of Internal Combustion Engines
,”
NDIA Ground Vehicle Systems Engineering and Technology Symposium
, Novi, MI, Aug.
8
10
.https://events.esd.org/wp-content/uploads/2017/08/Advanced-Modelingand-Optimization-for-Virtual-Calibration-of-Internal-Combustion-Engines.pdf
16.
Nishio
,
Y.
,
Murata
,
Y.
,
Yamaya
,
Y.
, and
Kikuchi
,
M.
,
2018
, “
Optimal Calibration Scheme for Map-Based Control of Diesel Engines
,”
Sci. China Inf. Sci.
,
61
(
7
), pp.
1485
1496
.10.1007/s11432-017-9381-6
17.
Gao
,
J.
,
Zhang
,
Y.
, and
Shen
,
T.
,
2017
, “
An on-Board Calibration Scheme for Map-Based Combustion Phase Control of Spark-Ignition Engines
,”
IEEE/ASME Trans. Mechatron.
,
22
(
4
), pp.
1485
1496
.10.1109/TMECH.2017.2696788
18.
Malikopoulos
,
A. A.
,
Papalambros
,
P. Y.
, and
Assanis
,
D. N.
,
2007
, “
A Learning Algorithm for Optimal Internal Combustion Engine Calibration in Real Time
,”
ASME
Paper No. DETC2007-34718.10.1115/DETC2007-34718
19.
Guardiola
,
C.
,
Pla
,
B.
,
Bares
,
P.
, and
Waschl
,
H.
,
2016
, “
Adaptive Calibration for Reduced Fuel Consumption and Emissions
,”
Proc. Inst. Mech. Eng., Part D: J. Automob. Eng.
,
230
(
14
), pp.
2002
2014
.10.1177/0954407016636977
20.
Guardiola
,
C.
,
Climent
,
H.
,
Pla
,
B.
, and
Reig
,
A.
,
2017
, “
Optimal Control as a Method for Diesel Engine Efficiency Assessment Including Pressure and NOx Constraints
,”
Appl. Therm. Eng.
,
117
, pp.
452
461
.10.1016/j.applthermaleng.2017.02.056
21.
Luján
,
J. M.
,
Guardiola
,
C.
,
Pla
,
B.
, and
Reig
,
A.
,
2019
, “
Optimal Control of a Turbocharged Direct Injection Diesel Engine by Direct Method Optimization
,”
Int. J. Engine Res.
,
20
(
6
), pp.
640
652
.10.1177/1468087418772231
22.
Ma
,
H.
,
Li
,
Z.
,
Tayarani
,
M.
,
Lu
,
G.
,
Xu
,
H.
, and
Yao
,
X.
,
2019
, “
Model-Based Computational Intelligence Multi-Objective Optimization for Gasoline Direct Injection Engine Calibration
,”
Proc. Inst. Mech. Eng., Part D: J. Automob. Eng.
,
233
(
6
), pp.
1391
1402
.10.1177/0954407018776743
23.
Shen
,
X.
,
Zhang
,
Y.
,
Shen
,
T.
, and
Khajorntraidet
,
C.
,
2017
, “
Spark Advance Self-Optimization With Knock Probability Threshold for Lean-Burn Operation Mode of SI Engine
,”
Energy
,
122
, pp.
1
10
.10.1016/j.energy.2017.01.065
24.
Ma
,
H.
,
Xu
,
H.
,
Wang
,
J.
,
Schnier
,
T.
,
Neaves
,
B.
,
Tan
,
C.
, and
Wang
,
Z.
,
2015
, “
Model-Based Multiobjective Evolutionary Algorithm Optimization for HCCI Engines
,”
IEEE Trans. Veh. Technol.
,
64
(
9
), pp.
4326
4331
.10.1109/TVT.2014.2362954
25.
Tan
,
Q.
,
Divekar
,
P.
,
Tan
,
Y.
,
Chen
,
X.
, and
Zheng
,
M.
,
2018
, “
Model-Guided Extremum Seeking for Diesel Engine Fuel Injection Optimization
,”
IEEE/ASME Trans. Mechatron.
,
23
(
2
), pp.
936
946
.10.1109/TMECH.2018.2793879
26.
Malikopoulos
,
A. A.
,
Assanis
,
D. N.
, and
Papalambros
,
P. Y.
,
2009
, “
Real-Time Self-Learning Optimization of Diesel Engine Calibration
,”
ASME J. Eng. Gas Turbines Power
,
131
(
2
), p.
022803
.10.1115/1.3019331
27.
Gupta
,
R.
,
Kolmanovsky
,
I. V.
,
Wang
,
Y.
, and
Filev
,
D. P.
,
2012
, “
Onboard Learning-Based Fuel Consumption Optimization in Series Hybrid Electric Vehicles
,” American Control Conference (
ACC
), Montreal, QC, Canada, June 27–29, pp.
1308
1313
.10.1109/ACC.2012.6314797
28.
Yusivar
,
F.
,
Hidayat
,
N.
,
Gunawan
,
R.
, and
Halim
,
A.
,
2014
, “
Implementation of Field Oriented Control for Permanent Magnet Synchronous Motor
,” International Conference on Electrical Engineering and Computer Science (
ICEECS
), Bali, Indonesia, Nov. 24–25, pp.
359
362
.10.1109/ICEECS.2014.7045278
29.
Drallmeier
,
J. A.
,
Solbrig
,
C. E.
,
Middleton
,
R. J.
,
Siegel
,
J. B.
, and
Stefanopoulou
,
A. G.
,
2022
, “
Maximizing Work Extraction Efficiency of a Hybrid Opposed Piston Engine Through Iterative Trajectory Optimization
,”
IFAC-PapersOnLine
,
55
(
24
), pp.
179
184
.10.1016/j.ifacol.2022.10.281
30.
Filev
,
D.
,
Wang
,
Y.
, and
Kolmanovsky
,
I.
,
2014
, “
Learning Based Approaches to Engine Mapping and Calibration Optimization
,”
Optimization and Optimal Control in Automotive Systems
,
Springer International Publishing
,
Cham, Switzerland
, pp.
257
272
.
31.
Naik
,
S.
,
Johnson
,
D.
,
Koszewnik
,
J.
,
Fromm
,
L.
,
Redon
,
F.
,
Regner
,
G.
, and
Fuqua
,
K.
,
2013
, “
Practical Applications of Opposed-Piston Engine Technology to Reduce Fuel Consumption and Emissions
,”
SAE
Paper No. 2013-01-2754.10.4271/2013-01-2754
You do not currently have access to this content.