Performance Enhancement of Semi-active Continuous Skyhook Control Using Chaotic Map Particle Swarm Optimization-Based Stability Augmentation System

Enhancing the performance of a ride-oriented algorithm to provide ride comfort and vehicle stability throughout different terrains is a challenging task. This article aims to improve the performance of the state-of-the-art continuous skyhook algorithm in coupled motion modes with an optimally tuned stability augmentation system (SAS). The tuning process is carried out using a chaotic map-initialized particle swarm optimization (C-PSO) approach with ride comfort and roll stability as a performance index. A large van model built-in CarSim is co-simulated with a C-PSO algorithm and control system designed in MATLAB. To realize the feasibility and effectiveness of the proposed system, a software-in-loop test is conducted on five complex ride terrains with different dominant vehicle body motion modes. The test results are compared against the passive system, four corner continuous skyhook control, and four corner type-1 fuzzy control. The test results confirm the effectiveness of the proposed system in providing better ride comfort, improved roll stability, good road holding, and eliminating the possibility of an untripped rollover. The results indicate a significant performance enhancement of CS-SAS against four corner continuous skyhook in ride road tests with an average root mean square (RMS) heave acceleration reduction of 28.41%. The results also exhibit distinct control effects on vehicle roll by mitigating the RMS-roll angle by an average of 61.52% for stability-based road tests.