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The Multiobjective Optimal Design Problems and their Pareto Optimal Fronts for Li-Ion Battery Cells
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 05, 2016 by SAE International in United States
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This paper begins with a baseline multi-objective optimization problem for the lithium-ion battery cell. Maximizing the energy per unit separator area and minimizing the mass per unit separator area are considered as the objectives when the thickness and the porosity of the positive electrode are chosen as design variables in the baseline problem. By employing a reaction zone model of a Graphite/Iron Phosphate Lithium-ion Cell and the Genetic Algorithm, it is shown the shape of the Pareto optimal front for the formulated optimization takes a convex form. The identified shape of the Pareto optimal front is expected to guide Design of Experiments (DOE) and product design. Compared with the conventional studies whose optimizations are based on a single objective of maximizing the specific energy, the proposed multi-objective optimization approach offers more flexibility to the product designers when trade-off between conflicting objectives is required. The solutions of the multi-objective optimization include multiple alternatives which may lead to more energy per unit separator area but result in larger weight or vice versa. These alternatives enable the product designers to choose the most appropriate design that best fits the characteristics of the application. Three design cases are employed to illustrate the wide applicability of the developed Pareto optimal front to common design problems in industry. Different objectives are adopted in the three cases to represent different appropriate applications for the cell to be designed, but all the three cases can be solved with the solutions for the baseline multi-objective problem.
CitationHong, Y. and Lee, C., "The Multiobjective Optimal Design Problems and their Pareto Optimal Fronts for Li-Ion Battery Cells," SAE Technical Paper 2016-01-1199, 2016, https://doi.org/10.4271/2016-01-1199.
- Scrosati, Bruno, and Jürgen Garche. "Lithium Batteries: Status, Prospects and Future." Journal of Power Sources: 2419-430.
- Scrosati, Bruno, Jusef Hassoun, and Yang-Kook Sun. "Lithiumion Batteries. A Look into the Future." Energy & Environmental Science Energy Environ. Sci.: 3287.
- Christen, Thomas, and Carlen Martin W.. "Theory of Ragone Plots." Journal of Power Sources: 210-16.
- Santhanagopalan, Shriram, Qingzhi Guo, Premanand Ramadass, and White Ralph E.. "Review of Models for Predicting the Cycling Performance of Lithium Ion Batteries." Journal of Power Sources: 620-28.
- Luo, Weilin, Chao Lyu, Lixin Wang, and Liqiang Zhang. "A New Extension of Physics-based Single Particle Model for Higher Charge-discharge Rates." Journal of Power Sources: 295-310.
- Newman, John. "Optimization of Porosity and Thickness of a Battery Electrode by Means of a Reaction-Zone Model." Journal of The Electrochemical Society J. Electrochem. Soc.: 97.
- Srinivasan, Venkat, and Newman John. "Design and Optimization of a Natural Graphite/Iron Phosphate Lithium-Ion Cell." Journal of The Electrochemical Society J. Electrochem. Soc.
- Chen, Y.-H., Wang C.-W., Zhang X., and Sastry A.m.. "Porous Cathode Optimization for Lithium Cells: Ionic and Electronic Conductivity, Capacity, and Selection of Materials." Journal of Power Sources: 2851-862.
- Methekar, Ravi N, Vijayasekaran Boovaragavan, Mounika Arabandi, Venkatasailanathan Ramadesigan, Subramanian Venkat R, Folarin Latinwo, and Braatz Richard D. "Optimal Spatial Distribution of Microstructure in Porous Electrodes for Li-ion Batteries." Proceedings of the 2010 American Control Conference.
- Golmon, Stephanie, Kurt Maute, and Dunn Martin L.. "A Design Optimization Methodology for Li Batteries." Journal of Power Sources: 239-50.
- Du, Wenbo, Amit Gupta, Xiangchun Zhang, Sastry Ann Marie, and Wei Shyy. "Effect of Cycling Rate, Particle Size and Transport Properties on Lithium-ion Cathode Performance." International Journal of Heat and Mass Transfer: 3552-561.
- Golmon, Stephanie, Kurt Maute, and Dunn Martin L.. "Multiscale Design Optimization of Lithium Ion Batteries Using Adjoint Sensitivity Analysis." International Journal for Numerical Methods in Engineering Int. J. Numer. Meth. Engng, 2012, 475-94.
- Stewart, Sarah G., Venkat Srinivasan, and Newman John. "Modeling the Performance of Lithium-Ion Batteries and Capacitors during Hybrid-Electric-Vehicle Operation." Journal of The Electrochemical Society J. Electrochem. Soc.
- Caramia, Massimiliano, and Paolo Olmo. Multi-objective Management in Freight Logistics Increasing Capacity, Service Level and Safety with Optimization Algorithms. London: Springer, 2008.
- Ngatchou, P., Zarei A., and El-Sharkawi A.. "Pareto Multi Objective Optimization." Proceedings of the 13th International Conference On, Intelligent Systems Application to Power Systems.
- Guo, Meng, Godfrey Sikha, and White Ralph E.. "Single-Particle Model for a Lithium-Ion Cell: Thermal Behavior." Journal of The Electrochemical Society J. Electrochem. Soc.
- Lee, Kwang Y. Modern Heuristic Optimization Techniques Theory and Applications to Power Systems. Hoboken, N.J.: Wiley ;, 2008.
- Deb, Kalyanmoy. Multi-objective Optimization Using Evolutionary Algorithms. Chichester: John Wiley & Sons, 2001.
- Amouzgar, Kaveh. "Multi-objective optimization using Genetic Algorithms." (2012).
- "Genetic Algorithm." - MATLAB. Accessed September 22, 2015.
- "Documentation." Find Minima of Multiple Functions Using Genetic Algorithm. Accessed September 22, 2015.
- "Documentation." Create Genetic Algorithm Options Structure. Accessed September 22, 2015.