Modeling and Optimization of Electrified Propulsion Systems
|Principal Investigator:||Zoran Filipi, Clemson University, firstname.lastname@example.org|
|Faculty:||Andrej Ivanco, Clemson University|
|Student:||Xueye (Anna) Zhang, Clemson University|
|Government:||Denise Rizzo, U.S. Army TARDEC|
|Industry:|| Bin Wu, Mercedes-Benz Hybrid LLC
Mengyang Zhang, Chrysler LLC
The impetus is provided by the Army’s and TARDEC’s emphasis on Vehicle Power and Energy systems. It’s driven by the need for fuel efficient tactical vehicles operating in the modern battlefield where endurance and resilience is one of the key parameters. In order to assure the technological advantage while maintaining the cost effectiveness of the future combat vehicles the cutting edge technology has to be deployed. An analysis of the novel hybrid propulsion systems can identify those opportunities, preselect the candidate vehicle configurations and accelerate their development.
The specific goals of this task are to:
- Develop a unified hybrid electric vehicle simulation framework for a series hybrid electric vehicle to be shared across the board. Including physics-based control oriented electric motor model for next-generation military medium trucks.
- Continue collaboration with the Prof. Hofmann (UM) and integrate computationally-efficient Finite-Element based models of Electric Machines into the Series-HEV simulation.
- Optimize electric motor sizing and design based on efficiency and hot-spot temperature predictions from the scalable physics-based e-motor model under real-world driving conditions.
- Investigate the impact of a demanding military vehicle driving missions on component duty cycles critical for new hybrid architectures control and design decisions
- Support the effort of Prof. Wagner (CU) in component thermal modeling and cooling system analysis. Integrate selected electrified accessories loads into the Vehicle Power and Energy System.
- Develop advanced supervisory control algorithms using approaches based on policy optimization and principles of self-learning. Enable optimization with multiple objectives.
- Zhang, X., A. Ivanco, X. Tao, J. Wagner, et al., "Optimization of the Series-HEV Control with Consideration of the Impact of Battery Cooling Auxiliary Losses", SAE Int. J. Alt. Power., 3(2):2014. doi:10.4271/2014-01-1904
- Zhou, K., A. Ivanco, Z. Filipi and H. Hofmann, "Finite Element Based Computationally Efficient Electric Machine Model Suitable for Integration in Electrified Vehicle Powertrain Design Optimization", IEEE, Applied Power Electronics Conference and Exposition (APEC), 2014. doi:10.1109/APEC.2014.6803520
- Ivanco, A., K. Zhou, H. Hofmann and Z. Filipi, "A Framework for Optimization of the Traction Motor Design Based on the Series-HEV System Level Goals", SAE International, 2014. doi:10.4271/2014-01-1801
- Ivanco, A., Filipi, Z., "Vehicle Modeling and Evaluation of the Engine Options in Conventional and Mild-Hybrid Powertrains", SAE paper 2013-01-1449, 2013 SAE World Congress, Detroit, 2013. doi:10.4271/2013-01-1449
- Marshall, B., Kelly, J., Lee, T.-K., Keoleian, G., Filipi, Z., “"Environmental assessment of plug-in hybrid electric vehicles using naturalistic drive cycles and vehicle travel patterns: A Michigan case study", Journal of Energy Policy, Vol. 58, pp. 358–370, July 2013. doi:10.1016/j.enpol.2013.03.037
- Patil, R.M.; Filipi, Z.; Fathy, H.K., "Comparison of Supervisory Control Strategies for Series Plug-In Hybrid Electric Vehicle Powertrains Through Dynamic Programming," Control Systems Technology, IEEE Transactions on , vol.22, no.2, pp.502,509, March 2014. doi: 10.1109/TCST.2013.2257778
- Lawler, B., Filipi, Z., "Integration of a Dual-Mode SI-HCCI Engine Into Various Vehicle Architectures", paper GTP12-1125, ASME Journal of Engineering for Gas Turbines and Power, Vol 135, Issue 5, 052802, 2013. doi:10.1115/1.4022990
- Kim, Y., Lee, T., and Filipi, Z., "Frequency Domain Power Distribution Strategy for Series Hybrid Electric Vehicles," SAE Int. J. Alt. Power. 1(1):208-218, 2012, doi:10.4271/2012-01-1003
- Lin, X., Ivanco, A., and Filipi, Z., "Optimization of Rule-Based Control Strategy for a Hydraulic-Electric Hybrid Light Urban Vehicle Based on Dynamic Programming," SAE Int. J. Alt. Power. 1(1):249-259, 2012, doi:10.4271/2012-01-1015
- Ivanco, A., Johri, R., and Filipi, Z., "Assessing the Regeneration Potential for a Refuse Truck Over a Real-World Duty Cycle," SAE Int. J. Commer. Veh. 5(1):364-370, 2012, doi:10.4271/2012-01-1030