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In this study, the enhancement of road friendliness of Heavy Goods Vehicle is investigated using two methods to control the resonant forces: (i) Determination of optimal asymmetric force velocity characteristics of the suspension dampers to control the wheel forces corresponding to the resonant modes; (ii) Optimal design of an axle vibration absorber to control the wheel forces corresponding to the unsprung mass resonance mode. An analogy between the dynamic wheel loads and ride quality performance characteristics of heavy vehicles is established through analysis of an in-plane vehicle model. A weighted optimization function comprising the dynamic load coefficient (DLC) and the overall rms vertical acceleration at the driver's location is formulated to determine the design parameters of the damper and absorber for a range of vehicle speeds. The results show that implementation of tuned axle absorbers can lead to reduction in the DLC ranging from 11.5 to 21%.

An articulated vehicle suspension comprising a parallel combination of passive energy restoring and dissipative elements and a feedback controlled force generator is analyzed using H2 control synthesis. The active suspension schemes based on limited-state measurements are formulated to minimize a performance measure comprising ride quality, cargo safety, suspension and tire dynamic deflections, and power requirements. The ride quality and the dynamic wheel load performance characteristics of these suspension schemes are compared to those of a vehicle with an ideal active suspension and an “optimum” passive suspension to demonstrate the performance potentials of the proposed limited-measurement-based suspension schemes.

A covariance analysis technique is proposed to derive the optimal suspension parameters of an articulated freight vehicle. A performance criteria comprising vehicle ride response, suspension deflections and tire deflections related to dynamic wheel loads, is formulated for the 9 degrees-of-freedom (DOF) in-plane model of the vehicle. The range of suspension parameters to achieve four different design requirements is identified and a parametric study is performed to make initial parameter selection using the covariance analysis. The optimal suspension parameters are then identified from the results of the study. The study concludes that the proposed technique can yield the optimal solution in a convenient and highly efficient manner.