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An accurate estimation of cycle-by-cycle in-cylinder mass and the composition of the cylinder charge is required for spark-ignition engine transient control strategies to obtain required torque, Air-Fuel-Ratio (AFR) and meet engine pollution regulations. Mass Air Flow (MAF) and Manifold Absolute Pressure (MAP) sensors have been utilized in different control strategies to achieve these targets; however, these sensors have response delay in transients. As an alternative to air flow metering, in-cylinder pressure sensors can be utilized to directly measure cylinder pressure, based on which, the amount of air charge can be estimated without the requirement to model the dynamics of the manifold.

Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

Fuel cell technology is recently becoming one of the most interesting fields for the car companies to invest in. This interest is because of their high efficiency and zero environmental pollution. Polymer electrolyte membrane fuel cells (PEMFC) are the most appropriate type of fuel cells for use in vehicles due to their low performance temperature and high power density. Air and fuel mass flow rate and partial pressure, fuel cell stack temperature, relative humidity of fuel cell membrane and heat and water management are the effective parameters of fuel cell power systems. Good transient behavior is one of the important factors that affect the success of fuel cell vehicles. In order to avoid stack voltage drop during transient condition, the control system of fuel cell vehicle is required to preserve optimal temperature, membrane hydration and partial pressure of reactants across the membrane. In this paper, we developed a dynamic model for fuel cell power system.