Automotive Science and Engineering

Artificial Neural Network Based Multi-Objective Evolutionary Optimization of a Heavy-Duty Diesel Engine

H. Shojaeefard

In this study the performance and emissions characteristics of a heavy-duty, direct injection, Compression ignition (CI) engine which is specialized in agriculture, have been investigated experimentally. For this aim, the influence of injection timing, load, engine speed on power, brake specific fuel consumption (BSFC), peak pressure (PP), nitrogen oxides (NOx), carbon dioxide (CO2), Carbon monoxide (CO), hydrocarbon (HC) and Soot emissions has been considered. The tests were performed at various injection timings, loads and speeds. It is used artificial neural network (ANN) for predicting and modeling the engine performance and emission. Multi-objective optimization with respect to engine emissions level and engine power was used in order to deter mine the optimum load, speed and injection timing. For this goal, a fast and elitist non-dominated sorting genetic algorithm II (NSGA II) was applied to obtain maximum engine power with minimum total exhaust emissions as a two objective functions.

Investigation of Wagon Derailment Moving on Cable-Stayed Bridge Due to Rail Irregularities

M. Jalili

Numerical Simulation of Combustion with Porous Medium in I.C. Engine

Mohammadi

Porous media has interesting features in compared with free flame combustion due to the extended of the lean flammability limits and lower emissions. Advanced new generation of internal combustion (IC) engines are expected to have far better emissions levels both gaseous and particulate matter, at the same time having far lower fuel consumption on a wide range of operating condition. These criteria could be improved having a homogeneous combustion process in an engine. Present work considers simulation of direct fuel injection in an IC engine equipped with a chemically inert porous medium (PM), having cylindrical geometry that is installed in cylinder head to homogenize and stabilize the combustion process. A numerical study of a 3D model, PM engine is carried out using a modified version of the KIVA-3V code. Since there is not any published material for PM-engines in literature, the numerical results for combustion waves propagation within PM are compared with experimental data available in the literature for a lean mixture of air and methane under filtration in packed bed, the accuracy of results are very promising. For PM-engine simulation the methane fuel is injected directly through a hot PM which is mounted in cylinder head. Therefore volumetric combustion occurs as a result within PM and in-cylinder. The effects of injection timing on mixture formation, pressure and temperature distribution in both phases of PM and incylinder fluid together with combustion emissions such as CO and NO are studied in detail for an important part of the cycle.

Vehicle Suspension Inspection by Stewart Robot

Kazemi

The suspension system of a vehicle is one of the most important parts which is involved in the process of vehicle designing. When a vehicle suspension system is designed, the evaluation of its performance against the road disturbances such as shocks and bumps are very important. The most commonly used systems consist of four hydraulic Jacks with mobility in vertical line with low speed and low exactitude. This paper offers a new mechanism for inspecting the suspension system of a vehicle using a parallel robot called Stewart. This robot is a special kind of parallel robots with capability of movements in different directions with high speed, accuracy and repeatability. In this paper the suspension system is evaluated on a quarter model of a simulated vehicle with control and guidance of Stewart robot using PID controller. The Stewart robot simulates the isolated and uneven bumps on a flat road in order to evaluate the given suspension system, and to investigate some criteria such as comforting of the passengers and remaining of the vehicle on the road. The results of the simulations show that the proposed method has a high accuracy, applicability and flexibility as well as simplicity, compared to currently used mechanisms.

Experimental Study on Diesel Exhaust Particles Agglomeration Using Acoustic Waves

R. Noorpoor

Diesel exhaust particles are a complex mixture of thousands of gases and fine substances that contain more than 40 different environmental contaminants. Being exposed to these exhaust particles (called soot) can cause lung damage and respiratory problems. Diesel particulate filters are used in many countries for mobile sources as a legal obligation to decrease harmful effect of these fine particles. The size range of these particles is varied from 0.01 to 1 µm. Moreover, it takes a long time to be settled when they are outspread in atmosphere. In this paper, homogeneous plane standing waves are used to coagulate nano particles in order to achieve larger size which has a better gravitational settling. It means that fine particles are converted into a large one. Theoretical mechanisms are studied which led to experimental results in 155(db) and 160 (db). The results show that acoustic precipitators have a good performance in removing fine particles in diesel exhaust. Additionally, they indicate that at high pressure levels, the system has high efficiency for removing fine particles

Lane Change Trajectory Model Considering the Driver Effects Based on MANFIS

Ghaffari

The lane change maneuver is among the most popular driving behaviors. It is also the basic element of important maneuvers like overtaking maneuver. Therefore, it is chosen as the focus of this study and novel multi-input multi-output adaptive neuro-fuzzy inference system models (MANFIS) are proposed for this behavior. These models are able to simulate and predict the future behavior of a Driver-Vehicle-Unit in the lane change maneuver for various time delays. To design these models, the lane change maneuvers are extracted from the real traffic datasets. But, before extracting these maneuvers, several conditions are defined which assure the extraction of only those lane change maneuvers that have a smooth and uniform trajectory. Using the field data, the outputs of the MANFIS models are validated and compared with the real traffic data. In addition, the result of these models is compared with the result of other trajectory models. This comparison provides a better chance to analyze the performance of these models. The simulation results show that these models have a very close compatibility with the field data and reflect the situation of the traffic flow in a more realistic way.

Balanced Scorecard with Fuzzy Inference as a Performance Measurement in an Automotive Manufacturing line

Hakimollahi

In recent years, the balanced score card (BSC) has been the focus of considerable methodology for strategic cost management in management accounting area since it was originally proposed by Kaplan ,R.S. and Norton, D.P. in 1992. BSC is an approach to performance measurement based on both financial and nonfinancial information from four perspectives which are called financial, customer, internal business process, and learning and growth, in order to balance the traditional financial performance system by several grouping of performance measures: short-term and long-term, internal and external, and current and future. Over time, it has been developed to a strategic management system from a comprehensive performance measure, and used in many organizations such as business, hospital, and autonomy in many countries. In this paper, we propose a general model based on BSC by introducing fuzzy inference mechanism. From this, specialists’ knowledge and experience can be effectively reflected during the construction of the practical model. Then we illustrate a practical example for an Automotive Manufacturing Co.