基因演算法於車輛懸吊系統最佳化之應用

Application of Genetic Algorithm on Optimization of Vehicle Suspension System

本研究係利用基因演算法（GA）進行車輛懸吊系統最佳化，具體而言是搜尋M998 悍馬車懸吊系統最佳主動控制參數及被動元件參數。主要研究內容包括三部份：第一部份是搜尋最佳主動控制參數，第二部份是搜尋最佳被動元件參數，第三部份是依第二部份所找到的最佳被動元件參數來搜尋最佳主動控制參數。電腦模擬分析結果顯示，最佳主動懸吊系統之舒適性可改善20﹪、操控性僅稍微惡化0.7﹪；與被動式懸吊系統比較，顯示利用主動式懸吊系統可明顯改善車輛之舒適性、操控性及懸吊系統工作行程。

In this research, genetic algorithms (GA) are applied to find the better parameters of M998 HMMWV suspension system for both active and passive elements. The study consists of three parts. The first part is to search the optimal parameters of active suspension elements. The second part is to find the best passive suspension parameters. In the last part, results of the second part are used to find the better parameters of active system. Computer simulations demonstrated that the best improvement is 20% for ride quality, while handling quality only deteriorates by 0.5%. The most important conclusion can be drawn from this research is that the proposed method can be used to improve both ride quality and suspension working space without seriously degrading handling quality.