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.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Adaptive Pulse Wave Imaging Automated Spatial Vessel Wall Inhomogeneity Detection in Phantoms and in-Vivo ABSTRACT: Imaging the mechanical characteristics of the artery wall may aid in the diagnosis of vascular
PROJECT TITLE : An Adaptive and Robust Edge Detection Method Based on Edge Proportion Statistics ABSTRACT: One of the most important preprocessing steps for high-level tasks in the field of image analysis and computer vision is
PROJECT TITLE : Learned Image Downscaling for Upscaling Using Content Adaptive Resampler ABSTRACT: SR models based on deep convolutional neural networks have shown greater performance in recovering the underlying high-resolution
PROJECT TITLE : Multipatch Unbiased Distance Non-Local Adaptive Means With Wavelet Shrinkage ABSTRACT: Many existing non-local means (NLM) approaches either utilise Euclidean distance to quantify the similarity between patches,
PROJECT TITLE : Depth Restoration From RGB-D Data via Joint Adaptive Regularization and Thresholding on Manifolds ABSTRACT: By integrating the properties of local and non-local manifolds that offer low-dimensional parameterizations

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry