In parallel to the developments in the fuel cell and hydrogen production, storage, and delivery technologies, fuel cell electric vehicles (FCEV) have started to take more attention; and several commercial products and prototypes have been already released. Modeling and simulation are important techniques to choose the design and operating parameters of the powertrain components of these vehicles and thus enhance their performance. This paper discusses, compares, and synthesizes different methods used for modeling vehicle dynamics and main powertrain components (fuel cell system, hydrogen storage unit, battery, transmission, electric motor, energy management system) as well as the drive cycle and life cycle simulations for FCEV. Rule-based and metaheuristic energy management methods for FCEV are discussed. Recent papers on the modeling and simulation of FCEV are categorized according to the powertrain components and methods used, and briefly discussed. The findings of this paper guide the researchers to select the optimum FCEV powertrain component types and their technical properties through modeling and simulation methods.

Fuel cell (FC) hybrid vehicle power trains are an attractive technology especially for automotive applications because of their higher efficiency and lower emissions compared to conventional vehicles. This study focuses on the design of an FC hybrid power train system and evaluation of its simulations for a given speed profile through two alternative power management algorithms (PMAs). Parameters suitable for a small vehicle were taken into consideration in the mathematical model of the vehicle. The proposed hybrid power train consists of an energy storage system, composed of a 4-kg battery pack (either lithium-ion (Li-ion) battery, nickel metal hydride, or nickel–cadmium) and a direct methanol fuel cell (DMFC) as the range extender. The PMAs basically aim to fulfill the power requirements of the vehicle and decide how to command the power split between the battery and the FC. The model comprising a DMFC, a battery, and PMAs was developed in MATLAB/Simulink environment. The polarization curve of the FC was obtained using a one-dimensional DMFC model. Vehicle power requirements for a drive cycle were calculated using the equations of longitudinal dynamics of vehicle, and the results were integrated into MATLAB/Simulink model. As a result of the simulations, methanol consumption, state of charge of the battery, and power output of the FC were compared for the PMAs. This comparison shows the effect of PMAs on the hybrid vehicle performance for three battery types. The results indicate that the vehicle range could be increased when proper strategy is used as PMA.