Cogent Engineering (Jan 2020)
Optimization of structural parameters through objective-evaluation of ride comfort in a heavy-duty commercial vehicle
Abstract
Dynamic behavior of vehicle systems and driving comfort is an optimization problem. Passive suspension system usage in design considerations is seen in heavy commercial vehicles where the owners are known to be highly cost conscious. Subjective evaluation of driving comfort by skilled drivers results from individual’s perceptions about vibrations with wide variations. Simulation methods and/or objective test measurements are used for finding the influence of vehicle structural parameters and operational parameters. Studies were conducted with objective of finding the minimum acceleration levels at driver seat for optimum driving comfort. In such research, full-vehicle model optimization needs complex simulations and iterations of the approximations to achieve optimum ride comfort. In this paper, cost-effective optimization of the suspension system design and geometry for a new vehicle application are explained. Structural design variables selected through simulation models have been evaluated with objective of achieving minimum acceleration at the driver seat. Orthogonal array method was applied for reducing the number of test configurations to six, from 48 possible combinations. The results obtained show the structural design parameter optimization by objective evaluation as effective for optimum ride comfort. Acceleration levels measured in test vehicle configuration with the shortest kingpin mounting location and progressive stiffness springs with damper at the rear-axle showed a significant improvement in ride comfort. No significant improvement was observed from different damper configurations in the front suspension. Thus, the ride comfort was enhanced with minimal changes only in the rear-axle suspension design parameters and optimization of vehicle hitching point geometry during the development of new vehicle application. It has been proposed to select variables through simulation, optimize the number of test configurations using orthogonal array and make an objective evaluation of the ride impact progressively based on successive test results.
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