Search Results

Modern two-stroke opposed-piston (OP2S) engines offer high efficiency and high power-to-weight ratio compared to conventional four-stroke (4S) engines. Oil consumption and high emissions are usually attributed to 2S engines. However, it is claimed that these drawbacks are well addressed in the modern OP2S engines. In this paper, a three-dimensional computational fluid dynamics (3D-CFD) model for combustion in an OP2S diesel engine was developed and validated against experimental data. The effects of injection parameters, such as the number of nozzles, spray angle, injector’s angle, injection pressure, and the start of injection (SOI), on emissions and performance, were investigated. By rotating one of the injectors by 45 degrees around its axis, it was found that NOX emission decreased by 20% and gross thermal efficiency (GTE) improved by 0.9%. In the case of injection pressure studies, by increasing the injection pressure up to 1600 bar, soot emission reduced by 7.7%.

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.

In this paper, an optimal control strategy is developed. The control strategy aims to simultaneously reduce fuel consumption and emissions of a parallel hybrid electric vehicle (HEV). A continuously variable transmission (CVT) is implemented in the HEV model. The CVT has a significant role to operate the internal combustion engine (ICE) near its optimal operating points; consequently its proper control will contribute to enhance the fuel economy and emissions. Using a trade-off between the fuel consumption and emission rates, improving the fuel consumption can cause the emission rates to be improved too. First, 5 different modes for the vehicle motion is defined. Afterwards, depending on the state of charge of the battery (SOC) and the requested power from the driver, the best mode, in each time step, is chosen. Knowing the best mode, the control strategy refers to ICE or electric motor (EM) pre-calculated optimal curves, and determines ICE/EM output speed (i.e. input speed to CVT).

In this paper, a mathematical model of the SCR catalytic converter is replaced with the neural network model to accelerate the optimization process. The Euro steady state calibration test data set is used to simulate the inlet properties of the SCR catalytic converter. For each chosen condition, a separate neural network is developed. In order to generate sufficient data to form a neural network for each condition, the original mathematical model was run several times at the temperature and inlet NOx concentration of each condition with a range of different ammonia concentrations. Subsequently, using MATLAB® software, the neural network model is trained and tested for each condition. Ammonia dosing optimization is performed using multi objective genetic algorithm module of MATLAB®. The optimization objectives are NOx reduction percentage and the outlet ammonia concentration of the SCR catalytic converter.

The desired performance of a spark ignition engine is highly related to the position of the spark advance, and consequently to the beginning of the stable combustion inside cylinder. The magnitude of the generated ion current signal, measured by a sensor inside cylinder, is closely correlated to the cylinder pressure magnitude. Their maximum values almost coincide at the same crank angle position. In this paper, a feedback control system is designed to fix the position of the maximum pressure at a given desired value of the crank angle. Noting that SI engines are highly nonlinear systems, a fuzzy logic controller is developed.

Today, an increasing emphasis is being placed on vehicle transient operation improvement to accomplish better drivability and lower emission and fuel consumption. In this regard, dynamic simulatory model of powertrain-vehicle is a stepping-stone on the path to achieve this goal. In this study, a complete powertrain-vehicle model has been developed to predict vehicle performance and fuel consumption, with careful attention given to the engine dynamics (dynamic of air and fuel flows into the intake manifold, and crankshaft transient response). The model has been experimentally identified and validated for “Paykan 1600i”. Since there is a good agreement between vehicle test and simulation results, the model proposed in this study can be used in design and performance evaluation of vehicle powertrain system.