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

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.

WH-MOEA: A Multi-Objective Evolutionary Algorithm for Wiener-Hammerstein System Identification. A Novel Approach for Trade-Off Analysis Between Complexity and Accuracy

“…It is possible to define an independent optimisation problem for each of these design concepts [38] and when they share the same objectives they can easily be compared directly in the objective space by simply comparing their respective Pareto fronts. For example in [39], this idea is used to compare alternative slide model control structures, in [40] to compare different loop pairings and in [41] to analyse the performance of different battery models. Figure 4 shows an example in which the Pareto fronts of three design concepts are compared in a two-dimensional objective space.…”

Identification of nonlinear processes based on Wiener-Hammerstein models and heuristic optimization.

“…It is possible to define an independent optimisation problem for each of these design concepts [68] and when they share the same objectives they can easily be compared directly in the objective space by simply comparing their respective Pareto fronts. For example in [104], this idea is used to compare alternative slide model control structures, in [45] to compare different loop pairings and in [82] to analyse the performance of different battery models. In this approach, an initial linear model is used as a starting point for nonlinear estimation.…”