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Dynamic Programming Versus Linear Programming Application for Charging Optimization of EV Fleet Represented by Aggregate Battery
Technical Paper
2018-01-0668
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This paper deals with a thorough analysis of using two fundamentally different algorithms for optimization of electric vehicle (EV) fleet charging. The first one is linear programming (LP) algorithm which is particularly suitable for solving linear optimization problems, and the second one is dynamic programming (DP) which can guarantee the global optimality of a solution for a general nonlinear optimization problem with non-convex constraints. Functionality of the considered algorithms is demonstrated through a case study related to a delivery EV fleet, which is modelled through the aggregate battery modeling approach, and for which realistic driving data are available. The algorithms are compared in terms of execution time and charging cost achieved, thus potentially revealing more appropriate algorithm for real-time charging applications.
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Citation
Skugor, B. and Deur, J., "Dynamic Programming Versus Linear Programming Application for Charging Optimization of EV Fleet Represented by Aggregate Battery," SAE Technical Paper 2018-01-0668, 2018, https://doi.org/10.4271/2018-01-0668.Data Sets - Support Documents
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References
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