A Benchmark Suite for Multi-Objective Optimization in Battery Thermal Management System Design

TL;DR

This paper introduces a specialized benchmark suite of real-world constrained multi-objective problems for optimizing Battery Thermal Management Systems, aiming to improve the evaluation of algorithms in practical engineering contexts.

Contribution

It develops a novel benchmark suite based on surrogate models for BTMS, filling a gap in realistic problem sets for multi-objective optimization in thermal management.

Findings

Provides a diverse set of real-world constrained problems

Facilitates more accurate evaluation of optimization algorithms

Lays groundwork for future benchmarking and analysis

Abstract

Synthetic Benchmark Problems (SBPs) are commonly used to evaluate the performance of metaheuristic algorithms. However, these SBPs often contain various unrealistic properties, potentially leading to underestimation or overestimation of algorithmic performance. While several benchmark suites comprising real-world problems have been proposed for various types of metaheuristics, a notable gap exists for Constrained Multi-objective Optimization Problems (CMOPs) derived from practical engineering applications, particularly in the domain of Battery Thermal Management System (BTMS) design. To address this gap, this study develops and presents a specialized benchmark suite for multi-objective optimization in BTMS. This suite comprises a diverse collection of real-world constrained problems, each defined via accurate surrogate models based on recent research to efficiently represent complex thermal-fluid interactions. The primary goal of this benchmark suite is to provide a practical and relevant testing ground for evolutionary algorithms and optimization methods focused on energy storage thermal management. Future work will involve establishing comprehensive baseline results using state-of-the-art algorithms, conducting comparative analyses, and developing a standardized ranking scheme to facilitate robust performance assessment.