Sensitivity stratification concept and hierarchical multi-objective optimisation for an ambulance with hydraulically interconnected suspension and stretcher-human body model. Issue 2 (1st February 2022)

• Record Type: Journal Article
• Authors: Tan, Bohuan; Wang, Shaohua; Zhang, Bangji; Li, Boyuan; Zhang, Nong; Qi, Hengmin
• Is Part Of: Vehicle system dynamics. Volume 60:Issue 2(2022)
• Page Start: 540
• Page End: 568
• Publication Date: 2022-02-01
• Subjects: Ambulance vehicle -- suspension -- human body model -- sensitivity analysis -- optimisation; Motor vehicles -- Dynamics -- Periodicals; Electronic journals; 629.231
• DOI: 10.1080/00423114.2020.1823432
• Languages: English
• ISSNs: 0042-3114

Abstract

Abstract : In this paper, a hierarchical optimization strategy for an ambulance with a supine human body model is proposed to improve suspension performance, where the ride comfort of both patients and paramedics and the road holding of the ambulance vehicle are particularly focused. An ambulance model integrating a hydraulically interconnected suspension system and a stretcher-human body model is developed first. This integrated model considers the interaction between stretcher and human body and provides a platform to directly evaluate ride comfort of patients. The sensitivity stratification concept is defined and the sensitivity levels of each design variable are determined according to sensitivity ratios. Then, design variables and optimization objectives are divided into two pairs and optimized in sequence, which not only comprehensively considers the overall performance of patients and paramedics, but also reduces the number of objectives in each optimization process. At last, the optimum solution of proposed hierarchical strategy is obtained and compared with general monolayer optimization strategy. The simulation results show that the hierarchical strategy is highly competitive and outperforms the monolayer optimization strategy, being able to provide not only a better solution and convergence but also has good computational efficiency.