Using a Multiobjective Approach to Compare Multiple Design Alternatives—An Application to Battery Dynamic Model Tuning

Alberto Pajares, Xavier Blasco, Juan Manuel Herrero and Raúl Simarro
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Alberto Pajares: Instituto Universitario de Automática e Informática Industrial (ai2), Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain
Xavier Blasco: Instituto Universitario de Automática e Informática Industrial (ai2), Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain
Juan Manuel Herrero: Instituto Universitario de Automática e Informática Industrial (ai2), Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain
Raúl Simarro: Instituto Universitario de Automática e Informática Industrial (ai2), Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain

Energies, 2017, vol. 10, issue 7, 1-19

Abstract: A design problem is usually solvable in different ways or by design alternatives. In this work, the term “concept” is used to refer to the design alternatives. Additionally, it is quite common that a design problem has to satisfy conflicting objectives. In these cases, the design problem can be formulated as a multiobjective optimization problem (MOP). One of the aims of this work was to show how to combine multiobjective requirements with concepts’ comparisons, in order to attain a satisfactory design. The second aim of this work was to take advantage of this methodology to obtain a battery model that described the dynamic behavior of the main electrical variables. Two objectives related to the model accuracy during the charge and discharge processes were used. In the final model selection, three different concepts were compared. These concepts differed in the complexity of their model structure. More complex models usually provide a good approximation of the process when identification data are used, but the approximation could be worse when validation data are applied. In this article, it is shown that a model with an intermediate complexity supplies a good approximation for both identification and validation data sets.

Keywords: multiobjective optimization; concept evaluation; battery model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
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