Title: Energy management strategy for fuel cell-battery vehicles based on fuzzy logic and dynamically focused learning method
Authors: Ehsan Katani; Mohsen Esfahanian; Saeed Behbahani
Addresses: Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran ' Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran ' Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran
Abstract: In regard to the energy crisis, FCHVs are one of the alternative options for conventional vehicles. One of the problems in HVs is retaining the state of charge (SoC) of the battery in driving conditions. In this paper, a new power management system with fuzzy logic controller and dynamically focused learning is used for reducing fuel consumption and retaining the SoC of the battery. The vehicle powertrain is modelled and simulated in Matlab-Simulink and advanced vehicle simulator software (ADVISOR). The results demonstrate that the proposed control strategy can satisfy the power requirement and retain the SoC of the battery in four different driving cycles. In addition, the results of the hybrid model are compared with default model in advisor with SoC correction. Finally, a well to wheel efficiency analysis is used on Samand vehicle to compare energy consumption, fuel cost and CO2 emission between proposed controller and common controller.
Keywords: dynamically focused learning; hybrid electric vehicles; HEVs; hybrid vehicles; fuzzy control; fuzzy logic controllers; FLCs; well to wheel analysis; state of charge; SoC correction; energy management; simulation; energy consumption; fuel costs; CO2; carbon dioxide; carbon emissions; vehicle emissions.
International Journal of Electric and Hybrid Vehicles, 2016 Vol.8 No.3, pp.270 - 287
Received: 20 Jul 2016
Accepted: 21 Jul 2016
Published online: 27 Oct 2016 *