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The Electro Gyro-Cator allows a driver to monitor his progress, plot and follow courses to a destination, select alternate routes, and drive more safely on unfamiliar roads or at night. Employing a sealed helium gas-rate gyro, the Electro Gyro-Cator offers visual display (CRT display) of a car's present location, direction and route, with overlay maps for fast, simple route selection and monitoring. The primary elements of the unit include trip and direction sensors, a 16-Bit central processing unit, a CRT display screen and a collection of transparent overlay maps fitted to the screen.

An essential feature of the Audi Quattro permanent four-wheel drive system is in the inter-axle differential located on the hollow output shaft in the gearbox: the drive is taken from this differential forward to the front differential through the inside of the hollow shaft, and rearward to a propellor shaft driving the rear differential. The major advantages in everyday driving include improved traction and a reduced tendency toward throttle induced changes of attitude. The greater traction allows not only better progress in difficult road conditions; it also gives better acceleration in difficult traffic situations, such as when joining a busy main road. The more easily predictable handling response to throttle changes means that Quattro vehicles have better tracking stability. Altogether, the active safety and "roadability" are considerably improved.

The objectives of the present work are to investigate the regulated and unregulated (particle) emissions of a classical and modern 2-stroke and a typical 4-stroke scooter with different ethanol blend fuels. There is also comparison of two different ethanol fuels: pure ethanol (E) *) and hydrous ethanol (EH) which contains 3.9% water and is denatured with 1.5% gasoline. Special attention is paid in this research to the hydrous ethanol, since the production costs of hydrous ethanol are much less than those for (dry) ethanol. The vehicles are with carburettor and without catalyst, which represents the most frequent technology in Eastern Asia and offers the information of engine-out emissions. Exhaust emissions measurements have been performed with fuels containing ethanol (E), or hydrous ethanol (EH) in the portion of 5, 10, 15 and 20% by volume. During the test systematical analysis of particle mass (PM) and nano-particles counts (NP) were carried out.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

This paper focuses on an assessment of predictive combustion model using a 0D/1D simulation tool under high load, different excess air ratio λ , and different combustion stabilities (based on coefficient of variation of indicated mean effective pressure COVimep). To consider that, crank angle resolved data of experimental pressure of 500 cycles are recorded under engine speed 1000 RPM and 2000 RPM, wide-open throttle, and λ=1.0, 1.42, 1.7, and 2.0. Firstly, model calibration is conducted using 18 cases at 2000 RPM using 500 cycle-averaged in-cylinder pressure to find optimized model constants. Then, the model constants are unchanged for other cases. Next, different cycle-averaged pressure data are used as inputs in the simulation based on the COVimep for studying sensitivity of the turbulent model constants. The simulation is conducted using 1D simulation software GT-Power.

A simulation method is presented for the analysis of combustion in spark ignition (SI) engines operated at elevated exhaust gas recirculation (EGR) level and employing multiple spark plug technology. The modeling is based on a zero-dimensional (0D) stochastic reactor model for SI engines (SI-SRM). The model is built on a probability density function (PDF) approach for turbulent reactive flows that enables for detailed chemistry consideration. Calculations were carried out for one, two, and three spark plugs. Capability of the SI-SRM to simulate engines with multiple spark plug (multiple ignitions) systems has been verified by comparison to the results from a three-dimensional (3D) computational fluid dynamics (CFD) model. Numerical simulations were carried for part load operating points with 12.5%, 20%, and 25% of EGR. At high load, the engine was operated at knock limit with 0%, and 20% of EGR and different inlet valve closure timing.

In order to comply with the existing emission norms of BSIII in India or EURO III and beyond that also, it is not sufficient to use the catalytic converter technology alone over the wide range of engine operating maps. Different studies across the world have proved that the cost, drivability, operating range against AFR, heat dissipation rate characteristics of catalytic converter limit their use in startup and idling conditions. One common way to tackle this condition is to use the Secondary Air Injection (SAI) system. In this system, small amount of air is injected after the exhaust port to initiate the thermal oxidation of gases. The right amount of air injected at the right time and at right location will reduce the emission by 37-90%. In the following study, SI engine vehicle with single cylinder, 160 cc and having carburetor is used as a test vehicle to evaluate the performance of SAI. The SAI system is modeled in AVL BOOST software and validated against the experimental data.