Title of article
Propulsion Capability Improvement and Fuel Consumption Reduction in Hybrid Electric Vehicles Utilizing Artificial Neural Networks
Author/Authors
nosohian, masih islamic azad university, tehran-north branch - department of electrical engineering, Tehran, Iran , riahi kashani, mohammad mansour islamic azad university, tehran-north branch - department of electrical engineering, Tehran, Iran , zaeri, amir hossein islamic azad university, shahin shahr branch - department of electrical engineering, Shahin Shahr, Iran
From page
1
To page
6
Abstract
This paper suggests an Artificial Neural Network model (ANN) in order to increase propulsion capability and reduce fuel consumption in hybrid electric vehicles. All stages are implemented by Simulink of MATLAB software. The simulation is based on basic parameters of internal-combustion engine. The achieved results reveal the ability of suggested method to reduce fuel consumption and increase the lifetime of the vehicle components, including the battery due to reduction of travel disturbances and soft moving of the vehicle at different speeds. It is also possible to optimize the problem for various vehicles and all types of roads by changing the motion parameters and conditions of artificial Neural Network Parameterization.
Keywords
Artificial Neural Network (ANN) , Internal Combustion Engine , Error Propagation Distances , Neural Network Efficiency
Journal title
Majlesi Journal of Mechatronic Systems
Journal title
Majlesi Journal of Mechatronic Systems
Record number
2572909
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