Dimensioning and configuration of EES systems for electric vehicles with boundary-conditioned adaptive scalarization

2013 International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS 2013

Volumn , Issue , 2013, Pages

  Chang, Wanli ^a   Lukasiewycz, Martin ^a   Steinhorst, Sebastian ^a   Chakraborty, Samarjit ^b  

^a TUM CREATE   (Singapore)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

HARDWARE; OPTIMAL SYSTEMS; PARETO PRINCIPLE;

AUTOMOTIVE MANUFACTURERS; ELECTRIC VEHICLES (EVS); ELECTRICAL ENERGY STORAGES; INTELLIGENT TRANSPORTATION; MULTI-OBJECTIVE OPTIMIZATION PROBLEM; OPTIMAL DESIGN; OPTIMAL SOLUTIONS; PARAMETER SPACES;

ELECTRIC VEHICLES;

EID: 84892630389     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CODES-ISSS.2013.6659013     Document Type: Conference Paper

References (42)

1. M. Lukasiewycz et al. System Architecture and Software Design for Electric Vehicles. In Proc. of DAC, 2013.
2. S. Lukic, J. Cao, R. Bansal, F. Rodriguez, and A. Emadi. Energy Storage Systems for Automotive Applications. IEEE Transactions on Industrial Electronics, 55(6):2258-2267, June 2008.
3. J. Molenda. Li-ion Batteries for Electric Vehicles. Annales UMCS, Chemistry, 66:23-36, 2011.
4. G. Berdichevsky, K. Kelty, JB Straubel, and E. Toomre. The Tesla Roadster Battery System. Tesla Motors Inc, 2006.
5. N. Takeda, S. Imai, Y. Horii, and H. Yoshida. Development of High-performance Lithium-ion Batteries for Hybrid Electric Vehicles. Mitsubishi Motors Technical Review, pages 68-72, 2003.
6. F. Koushanfar. Hierarchical hybrid power supply networks. In Proc. of DAC, 2010.
7. V. Pareto. Manuale di Economia Politica. Societa Editrice Libraria, Milano, Italy, 1906.
8. W. Stadler. A Survey of Multicriteria Optimization or the Vector Maximum Problem. Journal of Optimization Theory and Applications, 29(1):1-52, September 1979.
9. W. Cui and D. Tang. Electrospun Poly (Lithium 2-acrylamido-2- methylpropanesulfonic acid) Fiber-Based Polymer Electrolytes for Lithium-ion Batteries. Journal of Applied Polymer Science, 126:510-518, 2012.
10. B. Lalia, Y. Samad, and R. Hashaikeh. Nanocrystalline-Cellulose- Reinforced Poly (vinylideneuoride-co-hexauoropropylene) Nanocomposite Films as a Separator for Lithium Ion Batteries. Journal of Applied Polymer Science, 126:441-447, 2012.
11. 2 Nanotubes as Anode Electrode in Li-air and Li-ion Batteries. Current Applied Physics, 12:1580-1585, 2012.
12. 3=C Cathode Material for Lithium-ion Batteries. Journal of Alloys and Compounds, 536:132-137, 2012.
13. 2 and Its Application as Anode Materials for Lithium-ion Batteries. Journal of Alloys and Compounds, 536:179-183, 2012.
14. T. Duong. A Review of Lithium-ion Battery Properties of Plug-in Hybrid and Electric Vehicles in Light of Seminal Assumptions on the Viability of V2G. In Proc. of ISGT, 2012.
15. B. Dakyo and H. Gualous. Polynomial Control Method of DC/DC Converters for DC-Bus Voltage and Currents Management-Battery and Supercapacitors. IEEE Transactions on Power Electronics, 27(3):1455-1467, 2012.
16. J. Bocker, K. Witting, A. Seifried, and O. Znamenshchykov. Optimal Energy Management for a Hybrid Energy Storage System Combining Batteries and Double Layer Capacitors. In Proc. of ECCE, pages 1640-1647, 2009.
17. R. Hsu, C. Liu, and D. Chan. A Reinforcement-Learning-Based Assisted Power Management with QoR Provisioning for Human-Electric Hybrid Bicycle. IEEE Transactions on Industrial Electronics, 59(8):3350-3359, 2012.
18. E. Karden, S. Ploumen, B. Fricke, T. Miller, and K. Snyder. Energy Storage Devices for Future Hybrid Electric Vehicles. Journal of Power Sources, 168(1):2-11, 2007.
19. A. Khaligh and Z. Li. Battery, Ultracapacitor, Fuel Cell, and Hybrid Energy Storage Systems for Electric, Hybrid Electric, Fuel Cell, and Plug-In Hybrid Electric Vehicles: State of the Art. IEEE Transactions on Vehicular Technology, 59(6):2806-2814, 2010.
20. Y. Kim, S. Park, N. Chang, Q. Xie, Y. Wang, and M. Pedram. Networked Architecture for Hybrid Electrical Energy Storage Systems. In Proc. of DAC, 2012.
21. Y. Kim, S. Park, Y. Wang, and Q. Xie. Balanced Reconfiguration of Storage Banks in a Hybrid Electrical Energy Storage System. In Proc. of ICCAD, pages 624-631, 2011.
22. T. Markel and A. Simpson. Plug-In Hybrid Electric Vehicle Energy Storage System Design. In Proc. of Advanced Automotive Battery Conference, 2006.
23. M. Pedram, N. Chang, Y. Kim, and Y. Wang. Hybrid Electrical Energy Storage Systems. In Proc. of ISLPED, pages 363-368, 2010.
24. Y. Wang, Y. Kim, Q. Xie, N. Chang, and M. Pedram. Charge Migration Effciency Optimization in Hybrid Electrical Energy Storage (HEES) Systems. In Proc. of ISLPED, pages 103-108, 2011.
25. B. Dandurand, P. Guarneri, G. Fadel, and M. Wiecek. Equitable Multi-Objective Optimization Applied to the Design of a Hybrid Electric Vehicle Battery. Journal of Mechanical Design, 135(4), 2013.
26. I. Das and J. Dennis. A Closer Look at Drawbacks of Minimizing Weighted Sums of Objectives for Pareto Set Generation in Multicriteria Optimization Problems. Structural Optimization, 14(1):63-69, August 1997.
27. R. Steuer. Multiple Criteria Optimization: Theory, Computation and Application. Wiley, New York, 1986.
28. I. Das and J. Dennis. Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems. SIAM Journal on Optimization, 8(3):631-657, 1998.
29. A. Charnes, W. Cooper, and R. Ferguson. Optimal Estimation of Executive Compensation by Linear Programming. Management Science, 1(2):138-151, 1955.
30. G. Saharidis and M. Ierapetritou. Resolution Method for Mixed Integer Bi-Level Linear Problems Based on Decomposition Technique. Journal of Global Optimization, 44(1):29-51, 2009.
31. L. Xiao and W. Sheng and Z. Mao. Soft Error Optimization of Standard Cell Circuits Based on Gate Sizing and Multi-Objective Genetic Algorithm. In Proc. of DAC, pages 502-507, 2009.
32. B. Landwehr. A Genetic Algorithm Based Approach for Multi-Objective Data-Flow Graph Optimization. In Proc. of ASPDAC, pages 355-358, 1999.
33. B. Xue, M. Zhang, and W. Browne. Particle Swarm Optimization for Feqture Selection in Classification: A Multi-Objective Approach. IEEE Transactions on Cybernetics, pages 1-16, 2013.
34. Y. Wu and Q. Fan and F. Wang. Application of Multi-Objective Particle Swarm Optimization in Automobile Transmission Design. In Proc. of ICIC, pages 215-218, 2010.
35. D. Mueller-Gritschneder, H. Graeb, and U. Schlichtmann. A Successive Approach to Compute the Bounded Pareto Front of Partical Multi-objective Optimization Problems. SIAM Journal on Optimization, 20(2):915-934, 2009.
36. I. Kim and O. Weck. Adaptive Weighted-Sum Method for Bi-Objective Optimization: Pareto Front Generation. Structural and Multidisciplinary Optimization, 29(2):149-158, 2005.
37. J. Dutta and C. Kaya. A New Scalarization and Numerical Method for Constructing the Weak Pareto Front of Multi-Objective Optimization Problems. Optimization, 60(8-9):1091-1104, 2011.
38. N. Hamada and Y. Nagata and S. Kobayashi and I. Ono. On Scalability of Adaptive Weighted Aggregation for Multiobjective Function Optimization. In Proc. of IEEE Globecom Workshops, pages 1102-1106, 2012.
39. N. Li and C. Xing and Z. Fei and J. Kuang. Adaptive Multi-Objective Optimization for Distributed Heterogeneous Networks. In Proc. of IEEE Globecom Workshops, pages 1102-1106, 2012.
40. D. Linden and T. Reddy. Handbook of Batteries, Third Edition. McGraw-Hill, 2002.
41. M. Uno and K. Tanaka. Accelerated Charge-Discharge Cycling Test and Cycle Life Prediction Model for Supercapacitors in Alternative Battery Applications. IEEE Transactions on Industrial Electronics, 59(12):4704-4712, 2012.
42. R. Haaren. Assessment of Electric Cars' Range Requirements and Usage Patterns based on Driving Behavior Recorded in the National Household Travel Survey of 2009. Technical Report, 2009.