Performance Comparison Between Differential Evolution and Bat Algorithm in P.I.D Tuning for Optimization of Speed Control on Parallel Hybrid Electric Vehicle

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Performance Comparison Between Differential Evolution and Bat Algorithm in P.I.D Tuning for Optimization of Speed Control on Parallel Hybrid Electric Vehicle

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Talakua, Eddy Lybrech / Dhaniswara, Erwin / Simson, Simson

In the last decade, there have been many means of transportation that use fuel oil (Internal Combustion Engine (ICE)). This has a serious impact on the environment due to the resulting pollutant gas emissions. One solution is the use of hybrid electric vehicles (HEV) as a replacement for vehicles that use ICE. One of the performances that a HEV must have is to have a stable speed when driving. In this research, several methods used in the metaheuristic algorithm in the disturbance observer have the advantage of describing the inverse model of the plant without creating a mathematical model. Testing was carried out by comparing two methods of metaheuristic algorithms, namely Differential Evolution and Bat Algirthm. The simulation results show that the method used on this HEV is to maintain its speed, so according to the test results it shows that the Differential Evolution method is the best method for controlling speed on a Parallel Hybrid Electic Vehicle.

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Title :

Performance Comparison Between Differential Evolution and Bat Algorithm in P.I.D Tuning for Optimization of Speed Control on Parallel Hybrid Electric Vehicle

Contributors:

Talakua, Eddy Lybrech (author) / Dhaniswara, Erwin (author) / Simson, Simson (author)

Publication date :

2024-01-31

Remarks:

doi:10.52005/fidelity.v6i1.202
Fidelity : Jurnal Teknik Elektro; Vol 6 No 1 (2024): Edition for January 2024; 64-74 ; Fidelity : Jurnal Teknik Elektro ; Vol 6 No 1 (2024): Edition for January 2024; 64-74 ; 2686-3642 ; 2686-3650 ; 10.52005/fidelity.v6i1

DOI :

https://doi.org/10.52005/fidelity.v6i1.202

Type of media :

Article (Journal)

Type of material :

Electronic Resource

Language :

English

Keywords :

Metaheuristic Algorithms , Internal Combustion , Engine PID control , Parallel Hybrid Electric , Vehicle

Classification :

DDC: