Automotive Science and Engineering
Volume:10 Issue: 2, Spring 2020

Intake and exhaust manifolds are among the most important parts in engine in which pressure loss phenomena has direct impact on with changing volumetric efficiency. In typical 1D simulation codes, the quantity of pressure loss is proportional to the fluid’s mean velocity by Pressure Loss Coefficient (Kp) value. This important coefficient which has substantial rule in engine simulation is usually determined using constant available values, extracted from complicated experiments (like Miller’s tests) in a specified situation. But these values are credible only in situations according to those tests. Coupling 3D simulations with 1D codes is a common method to gain accurate values of these coefficients but this deals with drastic high simulation costs. To address this problem, a more efficient way is replacing an algebraic relation, extracted from 3D calculations, instead of a constant value in 1D code. It’s obvious that in order to reach accurate coefficients in arbitrary conditions (geometric and flow specifications) determining the best numerical method is mandatory.  In present research, after investigating all 3D simulation aspects, six different selected numerical solutions have been implemented on four different bends in ANSYS Fluent.Results have been validated by comparing loss coefficient values of incompressible fluid (water) with Miller loss coefficient values and method with the most accurate and stable results has been discovered. It was found that all these methods are suitable in general (with less than 5% error in coefficient values) but solutions with structured grid and SST k-ω turbulence modeling represented better stability and accuracy.

This study uses real driving cycles of a city bus and a standard driving cycle “WLTP” to implement a full comparison for energy demand and fuel consumption for different propulsion systems (i.e., Diesel ICE, Fuel cell and Electric engines). To better understand the comparison, a life cycle assessment is conducted using “GREET” and “GHGenius” software, which represents a clear demonstration of side effects and emissions of each engine on the environment. The results show that for “WLTP” cycle the bus needs 2423kJ energy for traveling each kilometer while the averaged amount of energy for traveling one kilometer of real driving cycle reaches to 1708kJ. By computing total energy use of  an electric bus we conclude, electric buses use almost 58% of electric energy for driving and the rest is lost. Then fuel cell and internal combustion engine buses have energy efficiency of 36% and 24% respectively. Concerning LCA analysis, it becomes apparent that unlike efficiency, electric buses are not environmentally benign as fuel cell buses. LCA analysis showed that fuel cell buses that use steam reforming hydrogen production process are a cleaner option than electric buses. Finally, since diesel buses produce the most emission, especially CO2, and consume the most energy in the total life cycle, they have no advantage for public transportation fleet.

Today most countries, examine the problem of car pollution. They enacted laws to prevent environmental polluting cars. They also try to find out wither pollution standards are applied by cars manufacturers or not.  The purpose of this study is to rank domestically produced cars quality based on manufacturing technology and exhaust emissions. Variables HC, CO, O2, CO2, and λ are analyzed for 10 selected car types, and results are presented with a box chart and finally, the considered cars are ranked according to the scored values. In practice, regarding the results of pollution variable, domestically produced cars can be ranked in terms of pollution quality parameters.  According to the numeric range determined for each variable, a number is assigned to each car and finally, the average score is calculated for each car.

To reduce the harmful effects of fuel based engines new technologies in automotive industries have introduced. Combination of novel ball continuously variable transmission and hybrid technologies with the advantages of optimum controlling of power sources in the vehicle are the main topic of this paper by preparing a model of transmission using GT-Suite software. In order to determine the operation and responses of the proposed transmission, different operational modes, along with different inputs in term of speed, torque and ratio are presented. This research successfully demonstrates a new type of transmission which is developed to enjoy the benefits of combining technologies in vehicle drivetrain that features high torque capacity and desirable drivability. Main achievement of this paper is to show the operational modes of this system as well as ability to mode alteration during vehicle operation. Various steady and transient modes are studied in this paper using multi body modeling and it shows HBCVT can eliminate most limitation of parallel hybrid systems.

In this research, the separate and simultaneous effects of pilot-main injection dwell time, pilot fuel quantity, and hydrogen gas addition on combustion characteristics, emissions formation, and performance in a heavy-duty diesel engine were investigated. To conduct the numerical study, valid and reliable models such as KH-RT for the break-up, K-Zeta-F for turbulence, and also ECFM-3Z for combustion were used. The effects of thirty-one different strategies based on two variables such as pilot-main injection dwell time (20, 25, 30, 35, and 40 CA) and pilot fuel quantity (5, 10, and 15% of total fuel per cycle) on NDC and DHC were investigated. The obtained results showed that by decreasing pilot-main injection dwell time due to shorter combustion duration and higher MCP, MCT, and HRRPP, amounts of CO and soot emissions decreased at the expense of high NOx formation. Also, increasing pilot fuel quantity due to higher combustion temperature and less oxygen concentration for the main fuel injection event led to an increase of NOx and soot emissions simultaneously. The addition of H2 due to significant heating value has increased IP and improved ISFC at the expense of NOx emissions but considerably decreased CO and soot emissions simultaneously.

In this paper, an intelligent system based on a novel algorithm for pulling out is designed and implemented. Through processing images of the surroundings of a vehicle, this very algorithm detects the obstacles and objects which are likely to pose danger to the vehicle while pulling out.  Two different methods are integrated into this system to detect obstacles and objects.  The first method, which is called Support Vector Machine (SVM), detects a broad range of moving objects around the vehicle drawing on training datasets.  Whereas, in the second method, types of obstacles and objects are detected using the area of the moving object within range. The system in question is implemented using both methods whose performance are compared in terms of computation and image processing speed; SVM and object area methods detected 93% and 96% of vehicles respectively. The utilization of this algorithm can contribute to the safety of vehicles while executing pullout maneuver and decreased the probability of crashing into fixed and moving obstacles in the surroundings.  Results of this research will be available to be used in the design and development of parking control systems.