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Pressure variation during engine combustion generates torque fluctuation that is delivered through the driveline. Torque fluctuation delivered to the tire shakes the vehicle body and causes the body components to vibrate, resulting in booming noise. HKMC (Hyundai Kia Motor Company)’s TMED (Transmission Mounted Electric Device) type generates booming noises due to increased weight from the addition of customized hybrid parts and the absence of a torque converter. Some of the improvements needed to overcome this weakness include reducing the torsion-damper stiffness, adding dynamic dampers, and moving the operation point of the engine from the optimized point. These modifications have some potential negative impacts such as increased cost and sacrificed fuel economy. Here, we introduce a method of reducing lock-up booming noise in an HEV at low engine speed.

The Representative Interactive Flamelet(RIF) concept has been applied to numerically simulate the combustion processes and pollutant formation in the direct injection diesel engine. Due to the ability for interactively describing the transient behaviors of local flame structures with CFD solver, the RIF concept has the capabilities to predict the auto-ignition and subsequent flame propagation in the diesel engine combustion chamber as well as to effectively account for the detailed mechanisms of soot and NOx formation. In order to account for the spatial inhomogeneity of the scalar dissipation rate, the Eulerian Particle Flamelet Model using the multiple flamelets has been employed. Special emphasis is given to the turbulent combustion model which properly accounts for vaporization effects on turbulence-chemistry interaction.

In future automobiles, conventional hydraulic brakes can be removed and be replaced by electrically operated brakes called brake-by-wire. The brake-by-wire units such as EMB(Electro-Mechanical Brake) provide better performance in braking by directly controlling the brake motor and are environmentally friendly without hydraulic fluid. Since the brake is safety-critical, the EMB should be reliable in its lifetime and robust fault diagnosis techniques should be included. Many researches have been carried out to develop the diagnosis techniques to improve their robustness and reliability. In this study, a fault size detection method is proposed with the parity space approach for the EMB system. In order to detect and isolate sensor faults from the residual, the residual generator is constructed. The model-based fault diagnosis system is developed for the EMB sensors; current sensor, position (or speed) sensor and clamping force sensor.

In the past few years, considerable efforts have been directed towards the further development of Urea-SCR(selective catalytic reduction) technique for diesel-driven vehicle. Although urea possesses considerable advantages over Ammonia(NH3) in terms of toxicity and handling, its necessary decomposition into Ammonia and carbon dioxide complicates the DeNOx process. Moreover, a mobile SCR system has only a short distance between engine exhaust and the catalyst entrance. Hence, this leads to not enough residence times of urea, and therefore evaporation and thermolysis can not be completed at the catalyst entrance. This may cause high secondary emissions of Ammonia and isocyanic acid from the reducing agent and also leads to the fact that a considerable section of the catalyst may be misused for the purely thermal steps of water evaporation and thermolysis of urea.

The development of autonomous vehicle requires the state-of-the-art technologies in perception, planning, control, and system integration. This paper presents an overview of the system architecture and software architecture of autonomous vehicles for system integration. Network based system architecture in this paper provides a distributed computing system for autonomous driving. Further, a real-time path planning and a target speed generation are described based on the curvilinear coordinate system. The design of a path in the curvilinear coordinate system stretches the design space as like the Cartesian coordinate system to simplify the generation of the path. In determination of target speed, curvatures and risk of a generated path were utilized for safe autonomous driving.

In Engine Management System, more accurate control is required to improve engine performance. Especially generating the precise ignition signal has a direct effect on better engine performance. In the beginning of this paper, a basic software structure to synchronize the engine crank signal and generate ignition signals will be explained. Several cases which can generate dwell timing error will be introduced based on this software structure. In addition, each impact level for each error case will be described. For cases of major error, compensation ways will be proposed in order to obtain more accurate dwell timing. The compensation ways by both microcontroller hardware and user software will be explained in detail. In conclusion, this paper will show the accuracy of ignition signal which implements proposed compensation ways that can be improved as compared to conventional ignition signal.

In this study, the effects of fuel injection on in-cylinder flow under various injection conditions were investigated using particle image velocimetry measurements in a two-cylinder, direct-injection spark-ignition, optically accessible engine with a spray-guided injection system. Various injection timings and pressures were applied to intensify the turbulence of in-cylinder flow. Simple double-injection strategies were used to determine how multiple injections affect in-cylinder flow. The average flow speed, turbulent kinetic energy, and enhancement level were calculated to quantitatively analyze the effects of fuel injection. Fuel injection can supply additional momentum to a cylinder. However, at an early injection timing such as 300° before top dead center, in-cylinder flow development could be disturbed by fuel injection due to piston impingement and interactions between the spray and air.

After the COVID-19 pandemic, leisure activities and cultures have undergone significant transformations. Particularly, there has been an increased demand for outdoor camping. Consequently, the need for capabilities that allow vehicles to navigate not only paved roads but also unpaved and rugged terrains has arisen. In this study, we aim to address this demand by utilizing AI to introduce a 'Stuck Probability Estimation Algorithm' for vehicles on off-road. To estimate the 'Stuck Probability' of a vehicle, a mathematical model representing vehicle behavior is essential. The behavior of off-road driving vehicles can be characterized in two main aspects: firstly, the harshness of the terrain (how uneven and rugged it is), and secondly, the extent of wheel slip affecting the vehicle's traction.