Background: The control system of the vehicle regulates parameters like fuel flow control, vehicle speed control, tracking, etc Objective: The main objective of the paper is to monitor and determine an efficient, and automated control system for an H-CNG-powered vehicle. Using neural networks and machine learning, we would develop an algorithm for the controller to regulate the speed of the car with the help of variables involved during the runtime of the vehicle. Methods: Initially, Generating a dataset with the help of formulation and computation for training. Further, analysing different supervised machine learning algorithms and training the Artificial Neural Network (ANN) using the generated dataset to predict and track the gains of the H-CNG vehicle accurately. Results: Analysis of the gains of the H-CNG vehicle are presented to understand the precision of the trained Neural Network. Conclusion: The final verdict of the paper is that the Neural Network is successful in tracking the gains of the H-CNG vehicle with the help of the dataset presented for training using the Random Forest Regression technique for machine learning.
Objective: This study aims to analyze the stability of Hydrogen-CNG powered vehicles. Hydrogen has the potential to be one of the most sustainable fuels of the future, decrease the global dependence on fossil fuel resources, and lower the pollutant emissions from the transportation industry. Though we have alternative non-conventional sources of energy, the perfect one to use as the energy source for vehicles is hydrogen. The mixture of Hydrogen and CNG provides excellent properties as fuel for transportation. A fast and accurate control system is designed that allows the combustion of pure Hydrogen. Methods: Combination of Hydrogen with CNG can increase the power and efficiency of the vehicle. The vehicle powered by Hydrogen-CNG needs an electronic control system assuring the operation of its discrete components. MIMO system models having brakes and acceleration inputs are considered. Results: Results are presented for the vehicle transfer function in the form of Bode plots, Root locus, and Routh Hurwitz judging the stability of the vehicle. result: The results are obtained in the form graphs which are further studied and used to determine the various aspects for stability of the system. Both the methods successfully analyze the system to be Stable over the criteria used for determining the stability (ωgc<ωpc). Conclusion: The main goals of the paper that is to analyze the stability of the vehicle and design an efficient control system are achieved. Obtaining the transfer function for governing equations for understanding the stability of the plant and generating a visual representation showing the relation between the variable quantities have been achieved in this paper.
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