University of Bahrain
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Speed Control of Hybrid Electric Vehicle Using Artificial Intelligence Techniques

Show simple item record Kaur,Japjeet Gaur, Prerna Saxena , Piyush Kumar,Vikas 2018-08-01T06:00:27Z 2018-08-01T06:00:27Z 2014
dc.identifier.issn 2210-1519
dc.description.abstract Growing concerns regarding toxic COx and NOx emissions caused by the vehicles and the scarcity of over-exploited non-renewable resources that led the automobile industry to look out for a more energy efficient energy consumption is the main reason behind the development of Hybrid Electric Vehicles (HEVs). This paper comprises of artificial intelligence techniques employed to achieve smooth speed tracking performance in nonlinear HEVs. Techniques like fuzzy logic, neural network and genetic algorithm have been applied to tune and optimize the parameters of Proportional-Integral-Derivative (PID) controller. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri *
dc.subject Hybrid Electric Vehicle
dc.subject Artificial Intelligence techniques
dc.subject PID controller
dc.subject optimization
dc.subject Fuzzy logic
dc.subject Neural Networks
dc.subject Genetic Algorithm
dc.title Speed Control of Hybrid Electric Vehicle Using Artificial Intelligence Techniques en_US
dc.type Article en_US
dc.volume 02
dc.issue 01
dc.source.title International Journal of Computing and Network Technology
dc.abbreviatedsourcetitle IJCNT

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