The increasing popularity of motorcycles has led to a growing concern for their better perform- ance. They are exposed to random vibrations from engine loads and road irregularities, affecting both ride comfort and motorcycle handling. This paper presents a study on the use of electrorhe- ological elastomers (EREs) as tunable engine mounts to improve motorcycles performance. First, a six degree of freedom (DoF) model is provided for a motorcycle system equipped with ERE engine mounts. The eigenvalue problem is then solved to identify the natural frequencies of the system. Both engine excitation and road irregularities are modeled as random signals, allowing for a real- istic assessment of the problem. Ride comfort is evaluated using frequency-weighted acceleration, to address the body’s sensitivity to various excitation frequencies. Moreover, the evaluation of the road holding index is performed by calculation of the tire-road interacting forces. To reflect real- world conditions, three missions (off-road, urban, and highway) are defined using a Beta probab- ility density function to capture variations in speed and road quality. Numerical random vibra- tion analysis is performed for each mission. A cost function is then introduced to provide a bal- ance between these two indices, and the optimization is carried out via the genetic algorithm. Results show that optimized ERE engine mounts significantly improve both ride comfort and road holding. On this basis, the main contributions of this paper are introducing and parametrically identifying tunable ERE-based engine mounts within a coupled motorcycle-engine-rider random- vibration model, and developing a frequency-domain random-vibration and optimization frame- work that simultaneously accounts for road and engine excitations while tuning mount properties for ride comfort and road holding. These findings highlight the potential of tunable ERE mounts, combined with systematic optimization, in advancing motorcycle vibration attenuation.

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