A Novel Methodology Proposed for Optimizing the Degree of Hybridization in Parallel HEVs using Genetic Algorithm

Authors: K. Varesi, A. Radan

Abstract:

In this paper, a new Genetic Algorithm (GA) based methodology is proposed to optimize the Degree of Hybridization (DOH) in a passenger parallel hybrid car. At first step, target parameters for the vehicle are decided and then using ADvanced VehIcle SimulatOR (ADVISOR) software, the variation pattern of these target parameters, across the different DOHs, is extracted. At the next step, a suitable cost function is defined and is optimized using GA. In this paper, also a new technique has been proposed for deciding the number of battery modules for each DOH, which leads to a great improvement in the vehicle performance. The proposed methodology is so simple, fast and at the same time, so efficient.

Keywords: Degree of Hybridization (DOH), Electric Motor, Emissions, Fuel Economy, Genetic Algorithm (GA), Hybrid ElectricVehicle (HEV), Vehicle Performance

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1329861

References:

[1] I. J. Albert, E. Kahrimanovic, and A. Emadi, "Disel Sport Utility Vehicles With Hybrid Electric Drive Trains," Vhicular Technology, IEEE Transactions on., vol. 53, No. 4 pp. 1247-1256, July 2004.
[2] S. M. Lukic and A. Emadi, "Effects of Drivetrain Hybridization on Fuel Economy and Dynamic Performance of Parallel Hybrid Electric Vehicles," Vhicular Technology, IEEE Transactions on., vol. 53, No. 2 pp. 385-389, March 2004.
[3] B. M. Baumann, G. Washington, B. C. Glenn and G. Rizzoni, "Mechatronic Design and Control of Hybrid Electric Vehicles," Mechatronics, IEEE/ASME Transactions on, vol. 5, No. 1 pp. 58-72, March 2000.
[4] D. Buecherl, I. Bolvashenkov and H. -G. Herzog, "Verification of the Optimum Hybridization Factor as Design Parameter of Hybrid Electric Vehicles," Vehicle Power and Propulsion Conference, 2009. VPPC-09. IEEE, pp. 847-851.
[5] C. Holder and J. Gover, "Optimizing the Hybridization Factor for a Parallel Hybrid Electric Small Car," Vehicle Power and Propulsion Conference, 2006. VPPC'06. IEEE, pp. 1-5.
[6] D.E. Goldberg, Genetic Algorithms in Search, Optimization & Machine Learning, Addison Wesley, 1989.
[7] www.pngv.org