Open AccessInvestigation of Operational Efficiency using Stochastic Models for Electric propulsion in Ships
Author(s) -
Nayayana
Publication year - 2020
Publication title -
journal of electrical engineering and automation
Language(s) - English
Resource type - Journals
ISSN - 2582-3051
DOI - 10.36548/jeea.2020.2.004
Subject(s) - propulsion , automotive engineering , electrically powered spacecraft propulsion , traction motor , powertrain , electric motor , traction (geology) , train , fuel efficiency , engineering , reliability (semiconductor) , probabilistic logic , computer science , power (physics) , torque , aerospace engineering , mechanical engineering , physics , cartography , quantum mechanics , artificial intelligence , geography , thermodynamics
In various models of vehicle drive trains, issues such as improving electric propulsion reliability, environmental performance, and economic efficiency has been enabled by the recent developments in electric power engineering in terms of materials, equipment and technologies. The increasing requirements in ecological parameters, efficiency for fault tolerance and reliability, accurate selection of design features and type of electric propulsion drive as well as the limitations on the traction equipment weight and installation space are the important parameters for execution of the system approach. The automobile electric propulsion systems consisting of one or more traction motors and few generating elements and their operational efficiency are analysed by means of stochastic models. Aircrafts, hybrid cars, diesel-electric locomotives, arctic cargo ships and icebreakers are ideal platforms for implementation of the propulsion system. The load modes of traction electric motors, operational fuel consumption, energy output of thermal engines and several other probabilistic characters of operational processes and random factors that influence the simulation result accuracy cannot be evaluated using the deterministic approach.