The aim of the paper is to propose a new approach to forecast the energy consumption for the next day using the unique data obtained from a digital twin model of a building. In the research, we tested which of the chosen forecasting methods and which set of input data gave the best results. We tested naive methods, linear regression, LSTM and the Prophet method. We found that the Prophet model using information about the total energy consumption and real data about the energy consumption of the top 10 energy-consuming devices gave the best forecast of energy consumption for the following day. In this paper, we also presented a methodology of using decision trees and a unique set of conditional attributes to understand the errors made by the forecast model. This methodology was also proposed to reduce the number of monitored devices. The research that is described in this article was carried out in the context of a project that deals with the development of a digital twin model of a building.
The aim of the paper is to present the experimental results for material model of the sand, case of wet and dry probe. Since traction and side forces derivation methodology and tire-round interaction models for onroad vehicles are widely described, there is a lack of methods for off-road vehicles. The methodology, presented in this work, includes test in various ground conditions and different driving direction. Test results, presented in the paper were acquired for dry and humid sand, for various tire tilt angle. Traction and side forces were acquired and then will be used for black-box model parameters identification of the wheel-ground interaction.
KeywordsElectric drive, tire-ground interaction, wheel model. Wheel-surface model parameters estimation: sand humidity influence on traction effort of all-terrain unmanned vehicle Tomasz Czapla et al.
Since the wheel interaction with a certain terrain cases (asphalt, concrete) are known and well described in case of straightforward motion and non-slip and slip cornering conditions, the skid-steered wheeled vehicles case needs to be analyzed. Side-slip for various attack angle has to be investigated. The main area of interest of research that is shown in the project is energy demand calculation of skid-steered wheeled vehicles in various terrain conditions. Certain cases of all-electric vehicles with individual electric motors per wheel demand a precise assessment of longitudinal and lateral forces in order to perform the fully controlled turn. Experimental stand designed and developed by authors allows to test the wheel-surface interaction for various terrain conditions and different driving directions. Test data were acquired for dry and wet sand and granite pavement. Traction and side forces were acquired and used to identify the wheel-soil interaction model parameters for unpropelled wheel. Results in a form of time series including longitudinal and lateral forces show the relation between attack angle, load and surface conditions in terms of stick and slip phenomenon that is essential for skid-steering dynamics calculations. Measurement results are then used for calculation of longitudinal and lateral forces coefficients as a function of attack angle and vertical load. Test were performed in natural environment, thus they are affected by changeable conditions. Multiple runs are used for elimination of that influence. Described experiments are a part of the project that includes results generalization using test validated FEM model. Described work is not intended to develop new ground-tire interaction models, it is focused on numerically efficient traction effort calculation method for various conditions including passive mode—unpropelled wheel.
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