PROJECT TITLE :
Adaptive Estimation of Energy Factors in an Intelligent Convoy of Vehicles
Energy consumption of a vehicle is a factor of several environmental and driving conditions, like air flow density, road grade, and vehicle weight. Correct estimation of these factors influences the management performance, diagnostics, and the vehicle's overall energy consumption. Individual vehicle dynamics, as half of a big convoy governing principles, can expand to incorporate the states that are shared between vehicles. The controller performance depends on the estimated parameters to attenuate energy consumption. The estimation of environmental and driving conditions for individual vehicles as half of a convoy could be a difficult task. This paper introduces an adaptive model-based energy factor estimation in large-scale convoys. These factors are influenced by vehicle parameters and driving condition uncertainties. These uncertainties, if not estimated correctly, shift the expected energy consumption and result in low control performance. Mathematical formulation of the proposed estimator in the context of enormous-scale system is studied through many case study situations, and their effectiveness is demonstrated.
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