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In this work, we investigate a state estimation problem for a full-carsemi-active suspension system. To account for the complex calculation andoptimization problems, a vehicle-to- cloud-to-vehicle (V2C2V) scheme isutilized. Moving horizon estimation is introduced for the state estimationsystem design. All the optimization problems are solved in a remotely-embeddedagent with high computational ability. Measurements and state estimates aretransmitted between the vehicle and the remote agent via networkedcommunication channels. The effectiveness of the proposed method is illustratedvia a set of simulations.

Cloud-Aided State Estimation of A Full-Car Semi-Active Suspension System