This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Mission-based Design Space Exploration for Powertrain Electrification of Series Plugin Hybrid Electric Delivery Truck
Technical Paper
2018-01-1027
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
Hybrid electric vehicles (HEV) are essential for reducing fuel consumption and emissions. However, when analyzing different segments of the transportation industry, for example, public transportation or different sizes of delivery trucks and how the HEV are used, it is clear that one powertrain may not be optimal in all situations. Choosing a hybrid powertrain architecture and proper component sizes for different applications is an important task to find the optimal trade-off between fuel economy, drivability, and vehicle cost. However, exploring and evaluating all possible architectures and component sizes is a time-consuming task. A search algorithm, using Gaussian Processes, is proposed that simultaneously explores multiple architecture options, to identify the Pareto-optimal solutions. The search algorithm is designed to carefully select the candidate in each iteration which is most likely to be Pareto-optimal, based on the results from previous candidates, to reduce computational time. The powertrain of a medium-sized series plugin hybrid electric delivery truck with a range extender is optimized for different driving missions. Three different powertrain architectures are included in the design space exploration and the fuel economy is evaluated using a simulation model of the powertrain and Dynamic Programming. Results from the analysis show which ranges of powertrain component sizes are recommended for the different types of driving scenarios.
Recommended Content
Journal Article | Design of a Parallel-Series PHEV for the EcoCAR 2 Competition |
Technical Paper | System Design Model for Parallel Hybrid Powertrains using Design of Experiments |
Technical Paper | xEV Propulsion System Control-Overview and Current Trends |
Authors
Citation
Jung, D., Ahmed, Q., Zhang, X., and Rizzoni, G., "Mission-based Design Space Exploration for Powertrain Electrification of Series Plugin Hybrid Electric Delivery Truck," SAE Technical Paper 2018-01-1027, 2018, https://doi.org/10.4271/2018-01-1027.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 | ||
Unnamed Dataset 3 |
Also In
References
- Silvas , E. , Hofman , T. , Murgovski , N. , Etman , L.P. , and Steinbuch , M. Review of optimization strategies for system-level design in hybrid electric vehicles IEEE Transactions on Vehicular Technology 66 1 57 70 2017
- Josephson , J.R. , Chandrasekaran , B. , Carroll , M. , Iyer , N. , et al 1998
- Rizzoni , G. , Josephson , J.R. , Soliman , A. , Hubert , C. et al. Modeling, simulation, and concept design for hybrid-electric medium-size military trucks Proc. SPIE 5805 1 12 2005
- Vora , A.P. , Jin , X. , Hoshing , V. , Guo , X. et al. Simulation Framework for the Optimization of HEV Design Parameters: Incorporating Battery Degradation in a Lifecycle Economic Analysis IFAC-PapersOnLine 48 15 195 202 2015
- Ebbesen , S. , Elbert , P. , and Guzzella , L. Engine downsizing and electric hybridization under consideration of cost and drivability Oil & Gas Science and Technology-Revue d’IFP Energies nouvelles 68 1 109 116 2013
- Donateo , T. , Serrao , L. , and Rizzoni , G. Multi-objective optimization of a heavy-duty hybrid electric vehicle Strings 1 4.0 1 2007
- Zhou , Q. , Zhang , W. , Cash , S. , Olatunbosun , O. et al. Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization Applied Energy 189 588 601 2017
- Silvas , E. , Bergshoeff , E , Hofman , T. , and Steinbuch , M. Comparison of bi-level optimization frameworks for sizing and control of a hybrid electric vehicle Vehicle Power and Propulsion Conference (VPPC) 2014
- Shankar , R. , Marco , J. , and Assadian , F. The novel application of optimization and charge blended energy management control for component downsizing within a plug-in hybrid electric vehicle Energies 5 12 4892 4923 2012
- Pourabdollah , M. , Silvas , E. , Murgovski , N. , Steinbuch , M. et al. Optimal sizing of a series PHEV: Comparison between convex optimization and particle swarm optimization IFAC-PapersOnLine 48 15 16 22 2015
- Bayrak , A.E. , Kang , N. , and Papalambros , P.Y. Decomposition-based design optimization of hybrid electric powertrain architectures: Simultaneous configuration and sizing design Journal of Mechanical Design 138 7 071405 2016
- Pourabdollah , M. , Murgovski , N. , Grauers , A. , and Egardt , B. An iterative dynamic programming/convex optimization procedure for optimal sizing and energy management of PHEVs IFAC Proceedings 47 3 6606 6611 2014
- Pisu , P. , Koprubasi , K. , and Rizzoni , G. Energy management and drivability control problems for hybrid electric vehicles Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC'05 1824 1830 IEEE 2005
- Bayrak , A.E. , Yi , R. , and Papalambros , P.Y. Topology Generation for Hybrid Electric Vehicle Architecture Design Journal of Mechanical Design 138 8 081401 2016
- Zhuang , W. , Zhang , X. , Peng , H. , and Wang , L. Simultaneous optimization of topology and component sizes for double planetary gear hybrid powertrains Energies 9 6 411 2016
- Guzzella , L. and Sciarretta , A. Vehicle propulsion systems (Vol. 1) Berlin Heidelberg Springer-Verlag 2007
- Kotwicki , A. J. Dynamic models for torque converter equipped vehicles SAE Technical Paper 820393 1982 10.4271/820393
- Sundstrom , O. and Guzzella , L. 1625 1630 2009
- Hellström , E. , Ivarsson , M. , Åslund , J. , and Nielsen , L. Look-ahead control for heavy trucks to minimize trip time and fuel consumption Control Engineering Practice 17 2 245 254 2009
- Deb , K. Multi-objective optimization Search methodologies US Springer 2014 403 449
- Rasmussen , C. and Williams , C. Gaussian processes for machine learning 1 MIT press Cambridge 2006
- Osborne , M. A. , Garnett , R. , and Roberts , S. J. Gaussian processes for global optimization 3rd international conference on learning and intelligent optimization (LION3) 1 15 2009
- Jung , D. , Ahmed , Q. , and Rizzoni , G. Design Space Exploration for Powertrain Electrification using Gaussian Processes American Control Conference 2018 Milwaukee, USA
- Kelly , K. , Prohaska , R. , Ragatz , A. , and Konan , A. NREL DriveCAT - Chassis Dynamometer Test Cycles. National Renewable Energy Laboratory http://www.nrel.gov/transportation/drive-cycle-tool 2016