Development of simulation approach for CVT tuning using dual level genetic algorithm

Presented work aims to develop Genetic Algorithm (GA) based simulation approach for tuning of Continuously Variable Transmission (CVT). This study uses force balance to model the behaviour of CVT in MATLAB and employs dual level GA to optimize the tuning variables for desired output from CVT i.e. en...

Full description

Bibliographic Details
Main Author: Deepinder Jot Singh Aulakh
Format: Article
Language:English
Published: Taylor & Francis Group 2017-01-01
Series:Cogent Engineering
Subjects:
cvt
Online Access:http://dx.doi.org/10.1080/23311916.2017.1398299
id doaj-0046189de22c4cb793c5d81783bcb844
record_format Article
spelling doaj-0046189de22c4cb793c5d81783bcb8442021-03-02T14:46:46ZengTaylor & Francis GroupCogent Engineering2331-19162017-01-014110.1080/23311916.2017.13982991398299Development of simulation approach for CVT tuning using dual level genetic algorithmDeepinder Jot Singh Aulakh0NITPresented work aims to develop Genetic Algorithm (GA) based simulation approach for tuning of Continuously Variable Transmission (CVT). This study uses force balance to model the behaviour of CVT in MATLAB and employs dual level GA to optimize the tuning variables for desired output from CVT i.e. engagement of belt and sheaves at peak of engine torque curve, start of shifting at peak of engine power curve and keeping constant engine RPM (peak of power curve) during shifting. The variables for tuning are flyweight mass, primary and secondary spring stiffness and profile of primary and secondary cam. The results obtained from simulation are validated through experimental testing. The simulation results show good coherence with experiments in terms of engagement and shift starting RPM and also most of the shifting occurs at constant RPM. Also, the behaviour of CVT tuned by simulation is compared with the traditional method of experimental tuning and results obtained show that the simulation method is comparable to the traditional method in terms of accuracy. This study concludes with strong confidence in the potential of GA simulations for tuning.http://dx.doi.org/10.1080/23311916.2017.1398299cvtgenetic algorithmtuningsimulationforce balancefitness functionv belt
collection DOAJ
language English
format Article
sources DOAJ
author Deepinder Jot Singh Aulakh
spellingShingle Deepinder Jot Singh Aulakh
Development of simulation approach for CVT tuning using dual level genetic algorithm
Cogent Engineering
cvt
genetic algorithm
tuning
simulation
force balance
fitness function
v belt
author_facet Deepinder Jot Singh Aulakh
author_sort Deepinder Jot Singh Aulakh
title Development of simulation approach for CVT tuning using dual level genetic algorithm
title_short Development of simulation approach for CVT tuning using dual level genetic algorithm
title_full Development of simulation approach for CVT tuning using dual level genetic algorithm
title_fullStr Development of simulation approach for CVT tuning using dual level genetic algorithm
title_full_unstemmed Development of simulation approach for CVT tuning using dual level genetic algorithm
title_sort development of simulation approach for cvt tuning using dual level genetic algorithm
publisher Taylor & Francis Group
series Cogent Engineering
issn 2331-1916
publishDate 2017-01-01
description Presented work aims to develop Genetic Algorithm (GA) based simulation approach for tuning of Continuously Variable Transmission (CVT). This study uses force balance to model the behaviour of CVT in MATLAB and employs dual level GA to optimize the tuning variables for desired output from CVT i.e. engagement of belt and sheaves at peak of engine torque curve, start of shifting at peak of engine power curve and keeping constant engine RPM (peak of power curve) during shifting. The variables for tuning are flyweight mass, primary and secondary spring stiffness and profile of primary and secondary cam. The results obtained from simulation are validated through experimental testing. The simulation results show good coherence with experiments in terms of engagement and shift starting RPM and also most of the shifting occurs at constant RPM. Also, the behaviour of CVT tuned by simulation is compared with the traditional method of experimental tuning and results obtained show that the simulation method is comparable to the traditional method in terms of accuracy. This study concludes with strong confidence in the potential of GA simulations for tuning.
topic cvt
genetic algorithm
tuning
simulation
force balance
fitness function
v belt
url http://dx.doi.org/10.1080/23311916.2017.1398299
work_keys_str_mv AT deepinderjotsinghaulakh developmentofsimulationapproachforcvttuningusingduallevelgeneticalgorithm
_version_ 1724234834531844096