Electrical network optimization for electrically interconnected suspension system

Publication Name

Mechanical Systems and Signal Processing


The electrically interconnected suspension (EIS) can control vehicles' multiple-degree of freedom dynamics by designing a proper electrical network that connects independent electromagnetic suspensions. However, developing an electrical network (EN) for passive EIS to deal with complicated vibration is challenging. This paper proposes an EN optimization methodology for the EIS and experimentally validates the effectiveness of the optimized ENs with a hardware-in-the-loop (HIL) platform. First, a half-car model with a passive EIS is built and analysed for the EN design. The candidate EN structures are identified with an innovative method, which can cover all possible layouts with pre-determined complexity. Then, the optimization procedure of the EIS EN structures is determined to achieve a satisfactory level of ride comfort and handling stability. Finally, the optimized parameters of ENs are obtained with the genetic algorithm. In the HIL tests, the optimised ENs are validated with typical road vibration inputs and steering inputs. Experimental results demonstrate that a vehicle with optimized ENs can achieve better ride comfort and handling stability than vehicles with traditional passive suspension and unoptimized EIS electrical networks.

Open Access Status

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Funding Number


Funding Sponsor

Australian Research Council



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