Optimum structural design of the lower control arm using meta-heuristic algorithms

Abstract

In today's world, meta-heuristic methods are widely used to solve complex optimization problems in many different fields. Their most important advantage is their easy integration into different problems, allowing them to provide effective solutions to various issues. With the continuous development of algorithms, they have become an essential tool for optimization and design, offering efficient solutions to various problems. Particularly, the use of meta-heuristic algorithms is of significant importance in solving engineering design problems. This study focuses on obtaining the optimal design of the lower control arm, using meta-heuristic methods. Topology optimization followed by shape optimization was performed to achieve the optimal design. To obtain the optimal dimensions, a genetic algorithm and the newly developed osprey optimization algorithm from artificial intelligence optimization algorithms were used. This is the first application of the osprey optimization algorithm. When the optimization results are examined, the maximum stress of the lower control arm after topology optimization is 268 MPa. Its weight has been reduced from 1402 to 1281 g, a decrease of 8.6%. According to the genetic algorithm result, the maximum stress of the optimum control arm is 266.6 MPa. Its weight is calculated as 1201 g, which is 14.33% lighter than the current model. According to the Osprey optimization algorithm results, the maximum stress value of the lower control arm is 250.2 MPa and its weight is determined to be 1197.5 g. Thus, a suspension arm design 14.6% lighter than the initial model has been achieved with the osprey optimization algorithm.