Abstract
Longitudinal-connected air suspension has been proven to have desirable dynamic load-sharing performances for multi-axle heavy vehicles. However, optimization approaches towards the improvement of comprehensive vehicle performance through the geometric design of longitudinal-connected air suspension have been considerably lacking. To address this, based on a 5-degrees-of-freedom nonlinear model of a three-axle semi-trailer with longitudinal air suspension, taking the changes of driving conditions (road roughness, speed, and load) into account, a height control strategy of the longitudinal-connected air suspension was proposed. Then, in view of the height of the air spring under various driving conditions, the support vector regression method was employed to fit the relationship models between the performance indices and the driving conditions, as well as the suspension geometric parameters (inside diameters of the air line and the connectors). Finally, to tackle the uncertainties of driving conditions in the optimization of suspension geometric parameters, a double-loop multi-objective particle swarm optimization algorithm (DL-MOPSO) was put forward based on the interval uncertainty theory. The simulation results indicate that compared with the longitudinal-connected air suspension using two traditional geometric parameters, the optimization ratios for dynamic load sharing coefficient and root-mean-square acceleration at various spring heights are between −1.04% and 20.75%, and 1.44% and 35.1%, respectively. Therefore, based on the signals measured from the suspension height sensors, through integrated control of inflation/deflation valves of air suspensions, as well as the valves’ inside connectors and air lines, the proposed DL-MOPSO algorithm can improve the comprehensive driving performance of the longitudinal-connected three-axle semi-trailer effectively, and in response to changes in driving conditions.
Highlights
The suspension system of multi-axle trucks is an important component that affects the driving performance of vehicles
In order to improve the load-sharing and riding comfort of longitudinal-connected air suspension, suspension, a nonlinear model for a 5-DOF tri-axle semi-trailer with longitudinal-connected air a nonlinear model for a 5-DOF tri-axle semi-trailer with longitudinal-connected air suspension was suspension was formulated based on fluid mechanics and thermodynamics
The strategy for controlling the height of the longitudinal-connected air suspensions was designed according to road roughness, driving speed, and vehicle load
Summary
The suspension system of multi-axle trucks is an important component that affects the driving performance of vehicles. A more accurate nonlinear model of a tri-axle longitudinal-connected air suspension was formulated by Chen et al [16,17] Based on this model, the effects of driving conditions (road class, vehicle speed, and vehicle load) and air suspension parameters (static height and static absolute air pressure of air spring, inside diameters of air line and connector) on dynamic load-sharing were analyzed comprehensively. AtFinally, each based on the interval uncertainty theory, a DL-MOPSO algorithm is designed to optimize the inner diameters spring height, the relationships of the load-sharing and ride comfort indices with the changes of the conditions and suspension are fitted, respectively, based on support of the airdriving lines and connectors when theparameters driving conditions are changing. Comparing the optimized results with the results using conventional-sized longitudinal-connected air suspension, under the circumstances of various spring heights and driving conditions
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