Dynamic sensor zeroing algorithm of 6D IMU mounted on ground vehicles

The main focus of this paper is to compensate the steady state offset error of the 6D IMU which provides the measurements that include the vehicle linear accelerations and angular rates of all three axes. Additionally, the sensor compensation algorithm exploits the wheel speed data and the steering angle information, since they are already available in most of the modern mass production vehicles. These inputs are combined with the inverse vehicle kinematics to estimate the steady state offset error of each sensor inputs as it is done in a disturbance observer, and the raw sensor measurements are compensated by the estimated offset errors. The stability of the error dynamics regarding the integrated signal processing system is verified, and finally, the performance of the system is tested via experiments based on a real production SUV.     

Practically applicable devices for blocking the gap flow of a horn rudder to reduce rudder cavitation and their verification through numerical simulations

Rudder cavitation causes serious damage to the rudder and affects the safety and cost-effectiveness of a ship. In recent applications, a semicircular prismatic bar protruding beyond the concave surface of the horn facing the gap, located along the center-plane of the rudder, has been used to lessen the gap flow between the horn and the movable portion of the rudder system. Previous numerical studies with this single bar indicate that it can noticeably reduce rudder cavitation. In the present study, a pair of bars for blocking the vertical gaps, which are attached symmetrically to the center-plane on opposite convex surfaces of the movable portion, is suggested for circumventing the difficulties that arise in the practical application of single centre bars. Placed near the outer edges of the gap, the bars are are easily accessible at the maximum rudder angle to allow simple installation during routine ship maintenance. An additional blocking disk is inserted on top of the pintle block, blocking the horizontal gaps. Three-dimensional computations are conducted with these combined devices and the results show that the devices are remarkably efficacious in reducing rudder gap cavitation.     

In and out vision-based driver-interactive assistance system

The overall driving environment consists of the Traffic environment, vehicle and driver states (TVD). advanced driver assistance Systems (ADAS) must consider not only information on each of the TVD states but also their context. Recent research has focused on making more efficient and effective assistance systems by fusing all the information from the TVD states. Based on this research trend, this paper focuses on decision-level fusion to estimate the level of danger of a warning by using visual information of the traffic environment and the driver state. The driver state consists of the gazing region and the facial feature points that are obtained using the active appearance model (AAM). The traffic environment state consists of time to collision (TTC), time to lane Crossing (TLC), and lane color information, which are obtained from the environment in front of the vehicle, i.e., position of lanes and other vehicles. Warnings against lane-off, collision, and driver inattention are generated by fusing this vision-based information from inside and outside the vehicle. The experimental results prove that our vision-based interactive driver assistance system reduces most useless warnings.     

Performance of radial-type metal foam diesel particulate filters

An analytical study of the performance of a radial-type, metal foam diesel particulate filter is reported. A mathematical model for the filtration and regeneration of soot in a metal foam filter was developed. Nickel foam was selected for the filter medium due to its large specific area, high porosity, and high thermal resistance. For various metal foams, the filtration efficiency and the pressure drop through the filter were calculated, as was the deposition of soot. The results from the analytical model were compared with experimental data. In comparison with a conventional wall flow filter, the metal foam diesel particulate filter (DPF) is effective in utilizing the volume of material, due to the porous structures. As the size of the metal foam pores in the DPF increases from 580 μm to 800 μm, the filtration efficiency decreases from 90% to 50%, and the pressure drop decreases from 380 mbar to 20 mbar. The metal foam DPF with a large pore size is effective in utilizing the volume of material with a small pressure drop. The regeneration is completed within four minutes by the flow of hot exhaust gases under full load conditions.     

Investigation on Spray Behavior and NOx Conversion Characteristic of a Secondary Injector for a Lean NOx Trap Catalyst

Lean NOx trap (LNT) catalyst has been used to reduce NOx emissions from diesel engines. The LNT absorbs NOx in lean condition and discharges N2 by reducing NOx in rich conditions. Thus, it is necessary to make exhaust gas lean or rich conditions for controlling LNT system. For making a rich condition, a secondary injector was adopted to inject a diesel fuel into the exhaust pipe. In the case of secondary injector, the behavior of spray is easily affected by high temperature (i.e., 250 ～ 350 °C) occurred in the exhaust manifold. Therefore, it is needed to investigate the spray behavior of diesel fuel injected into an exhaust manifold, as well as the conversion characteristics for a lean NOx trap of a diesel engine with LNT catalyst. The characteristics of exhaust emissions in NEDC (New European Driving Cycle) mode were analyzed and spray behaviors were visualized in various exhaust gas conditions. The results show that as the exhaust gas mass flow increases, the spray cone angle becomes broad and the fuel is directed to the flow field. Besides, the cone angle of spray is decreased by centrifugal force caused in exhaust gas flow field. In addition, the effects of nozzle installation degree, injection quantity, and exhaust gas flow on NOx conversion performance were clarified.     

Testing and evaluation of a multi-commodity multi-modal network flow model for disaster relief management

The results of the testing of an optimization model in disaster relief management are presented. The problem is a large-scale multi-commodity, multi-modal network flow problem with time windows. Due to the nature of this problem, the size of the optimization model grows extremely rapidly as the number of modes and/or commodities increase. The formulation is based on the concept of a time-space network. Two heuristic algorithms are developed. One exploits an inherent network structure of the problem with a set of side constraints and the other is an interactive fix-and-run heuristic. The findings of the model-testing and a wide range of sensitivity analyses using an artificially generated data set are presented. Both solution procedures prove to be efficient and effective in providing close to optimal solutions.     

Combustion phase detection algorithm for four-cylinder controlled autoignition engines using in-cylinder pressure information

For several decades, the primary goal of the automotive industry has been to reduce harmful emissions and improve fuel economy. Gasoline engines are clean and powerful propulsion systems, but have poorer fuel economy than that of diesel engines. However, due to the development of new technologies such as variable valve timing and lift and direct gasoline injection, controlled autoignition (CAI) combustion can be realized. CAI engines combine the advantages of cleaner emissions and lower fuel consumption than conventional spark-ignition gasoline engines. In this study, a cylinder-pressure-based combustion phase detection method for CAI combustion is proposed. This method utilizes a normalized difference pressure (NDP), which is defined as the normalized pressure difference between the firing and motoring in-cylinder pressures. The proposed method was developed and validated with steady-state experimental data from an inline 4 cylinder, 2 L gasoline direct injection (GDI) CAI engine. Because the calculations in the NDP method are faster and simpler than in the conventional combustion phase detection method in CAI engines, this method can be embedded in a real-time controller. Furthermore, the proposed method displayed good accuracy in detecting the combustion phase and thus stabilized CAI combustion. Finally, the detailed experimental results are presented.     

Vision-based fusion of robust lane tracking and forward vehicle detection in a real driving environment

With the goal of developing an accurate and fast lane tracking system for the purpose of driver assistance, this paper proposes a vision-based fusion technique for lane tracking and forward vehicle detection to handle challenging conditions, i.e., lane occlusion by a forward vehicle, lane change, varying illumination, road traffic signs, and pitch motion, all of which often occur in real driving environments. First, our algorithm uses random sample consensus (RANSAC) and Kalman filtering to calculate the lane equation from the lane candidates found by template matching. Simple template matching and a combination of RANSAC and Kalman filtering makes calculating the lane equation as a hyperbola pair very quick and robust against varying illumination and discontinuities in the lane. Second, our algorithm uses a state transfer technique to maintain lane tracking continuously in spite of the lane changing situation. This reduces the computational time when dealing with the lane change because lane detection, which takes much more time than lane tracking, is not necessary with this algorithm. Third, false lane candidates from occlusions by frontal vehicles are eliminated using accurate regions of the forward vehicles from our improved forward vehicle detector. Fourth, our proposed method achieved robustness against road traffic signs and pitch motion using the adaptive region of interest and a constraint on the position of the vanishing point. Our algorithm was tested with image sequences from a real driving situation and demonstrated its robustness.     

Technology analysis and low-cost design of automotive radar for adaptive cruise control system

Recently, the advanced driver assistance system (ADAS), which helps mitigate car accidents, has been developed using environmental detection sensors, such as long and short range radar, lidar, wide dynamic range cameras, ultrasonic sensors and laser scanners. Among these detection sensors, radars can quickly provide drivers with reliable information about the velocity, distance and direction of a target obstacle, as well as information about the vehicle in changing weather conditions. In the adaptive cruise control system (ACCS), three radar sensors are usually needed because two short range radars are used to detect objects in the adjacent lane and one long range radar is used to detect objects in-path. In this paper, low-cost radar based on a single sensor, which can detect objects in both the adjacent lane and in-path, is proposed for use in the ACCS. Before designing the proposed radar, we analyzed the world-wide radar technology and market trends for ACCS. Based on this analysis, we designed a novel radar sensor for the ACCS using radar components, such as an antenna, transceiver module, transceiver control module and signal processing algorithm. Finally, target detection experiments were conducted. In the experimental results, the proposed single radar can successfully complete the detection required for the ACCS. In the conclusion, the perspective and issues in the future development of the ACCS radar are described.     

Control strategy for clutch engagement during mode change of plug-in hybrid electric vehicle

The plug-in hybrid electric vehicle (PHEV) has various driving modes used in both internal combustion engine and electric motors. The EV mode uses only an electric motor and the HEV mode uses both an engine and an electric motor. Specifically, when the PHEV of a pre-transmission parallel hybrid structure performs mode changing, its engine clutch is either engaged or disengaged, which is important in terms of ride comfort. In this paper, to enhance the mode changing process for the clutch engagement, a PHEV performance simulator is developed using MATLAB/Simulink based on system dynamics and experiment data. Vehicle driving analysis is carried out of the control logic and properties of the mode changing. A compensated torque is applied during the mode change. This results in the rapid speed synchronization with the clutch although the trade-off relationship of the mode change. In addition, the mode changing is conducted through the transmission shifting process to rapidly synchronize with speed. The control strategy implemented in this study is shown to improve the drivability and energy efficiency of a PHEV.