License plate extraction method for identification of vehicle violations at a railway level crossing

The primary cause of most railroad accidents is vehicle entry into railway level crossings despite warning messages. To identify drivers who violate railway level crossing regulations, vehicle license plate recognition can be applied at railway level crossings. The purpose of this paper is to present an effective method for extracting the license plate region from vehicle images taken at railway level crossings. The method proposed in this paper uses the variation in the gray-level values across the image of a license plate. For license plate region extraction, the character region is first recognized by identifying the character width and the difference between the background region and the character region. The license plate region is then extracted by finding the inter-character distance in the plate region. In addition, the license plate type is identified by the difference in the gray-level value between the background region and the character region. The proposed method is effective in solving the current challenges in extracting the license plate region from the damaged frames of license plates issued for domestic use, including new types of license plates. According to the experimental results, the proposed method yields a high extraction rate of 99.5% for vehicle license plates.     

Haptic steering support for driving near the vehicle’s handling limits; skid-pad case

Current vehicle dynamic control systems from simple yaw control to high-end active steering support systems are designed to primarily actuate on the vehicle itself, rather than stimulate the driver to adapt his/her inputs for better vehicle control. The driver though dictates the vehicle’s motion, and centralizing him/her in the control loop is hypothesized to promote safety and driving pleasure. Exploring the above statement, the goal of this study is to develop and evaluate a haptic steering support when driving near the vehicle’s handling limits (Haptic Support Near the Limits; HSNL). The support aims to promote the driver’s perception of the vehicle’s behaviour and handling capacity (the vehicle’s internal model) by providing haptic (torque) cues on the steering wheel. The HSNL has been evaluated in (a) driving simulator tests and (b) tests with a vehicle (Opel Astra G/B) equipped with a variable steering feedback torque system. Drivers attempted to achieve maximum velocity while trying to retain control in a circular skid-pad. In the simulator (a) 25 subjects drove a vehicle model parameterised as the Astra on a dry skid-pad while in (b) 17 subjects drove the real Astra on a wet skid-pad. Both the driving simulator and the real vehicle tests led to the conclusion that the HSNL assisted subjects to drive closer to the designated path while achieving effectively the same speed. With the HSNL the drivers operated the tires in smaller slip angles and hence avoided saturation of the front wheels’ lateral forces and excessive understeer. Finally, the HSNL reduced their mental and physical demand.     

Impact of hilly road information on fuel economy of FCHEV based on parameterization of hilly roads

Under real-life driving conditions, hilly roads are prevalent. Hilly road profile substantially influences fuel economy (FE) due to large impacts (increase or decrease) on power demand profile. Thus, the utilization of future altitude profile information has large potential to improve FE. In this paper, for optimal energy management of fuel cell hybrid electric vehicles (FCHEV), we investigate how much FE could potentially be improved when future altitude profile information is available. In particular, the simulation results are analyzed to justify the reason for this potential improvement and to identify which characteristics of hilly roads leads to large FE improvements. First of all, four statistical parameters are defined to characterize hilly roads: mean value, standard deviation (STD), distance interval (DI), and total distance. Then, several types of virtual hilly roads are generated based on various parameter combinations. In order to evaluate the potential FE improvement two energy management strategies (EMSs) are utilized: the first is Dynamic Programming, which evaluates the globally optimal FE when future hilly road information is available; the other is the Equivalent Consumption Minimization Strategy (ECMS) with adaptive equivalent factor for charge-sustenance, which represents the baseline EMS when future hilly road information is not available. The results show that downhill roads have much larger potential than uphill roads do for FE improvements when the future altitude profile is properly used for EMS. Furthermore, if the battery capacity is not large enough to handle the difference in potential energy, future hilly road information is more important to prevent violations of the maximum state-of-charge bound.     

Methodology for bus structure torsion stiffness and natural vibration frequency prediction based on a dimensional analysis approach

Engineering bus design requires testing of bus structures prototypes in order to guarantee a certain level of strength and an appropriate static and dynamic behavior of the bus superstructure when exposed to road loads. However, experimental testing of real bus structures is very expensive as it requires expensive resources and space. If testing is done on a scale bus model the previous required expenses are considerably reduced. Therefore, a novel methodology based on dimensional analysis applied to bus structure prediction to evaluate the bus structure static and dynamic performance is proposed. The static performance is evaluated attending to torsion stiffness and the dynamic in terms of the natural vibration frequencies and rollover threshold. A scale bus has been manufactured and dimensionless parameters have been defined in order to project the results obtained in the scale bus model to a larger model. Validation of the proposed methodology has been carried out under experimental and finite element analysis.     

Evaluation and visualization of stratified ultra-lean combustion characteristics in a spray-guided type gasoline direct-injection engine

To comply with reinforced emission regulations for harmful exhaust gases, including carbon dioxide (CO₂) emitted as a greenhouse gas, improved technologies for reducing CO₂ and fuel consumption are being developed. Stable lean combustion, which has the advantage of improved fuel economy and reduced emission levels, can be achieved using a sprayguided-type direct-injection (DI) combustion system. The system comprises a centrally mounted injector and closely positioned spark plugs, which ensure the combustion reliability of a stratified mixture under ultra-lean conditions. The aim of this study is to investigate the combustion and emission characteristics of a lean-burn gasoline DI engine. At an excess air ratio of 4.0, approximately 23% improvement in fuel economy was achieved through optimal event timing, which was delayed for injection and advanced for ignition, compared to that under stoichiometric conditions, while NO_x and HC emissions increased. The combustion characteristics of a stratified mixture in a spray-guided-type DI system were similar to those in DI diesel engines, resulting in smoke generation and difficulty in three-way catalystutilization. Although a different operating strategy might decrease fuel consumption, it will not be helpful in reducing NO_x and smoke emissions; therefore, alternatives should be pursued to achieve compliance with emission regulations.     

Realization of pmp-based control for hybrid electric vehicles in a backward-looking simulation

Optimal control is generally not possible without information about the future coming up, and it is not easy to obtain an optimal solution even though the information is given a priori. In this paper, a control concept based on Pontryagin’s Minimum Principle (PMP) is introduced as an efficient solution to generate an optimal control trajectory for Hybrid Electric Vehicles (HVEs) when the performance of the vehicles is evaluated on scheduled driving cycles at a simulation level. The main idea of the control concept is to minimize Hamiltonian, which is interpreted as equivalent fuel consumption, and the Hamiltonian is characterized by a co-state, which is interpreted as a weighting factor for the electrical usage. A key aspect of the control problem is that an appropriate initial condition of the co-state is required to satisfy the boundary condition of the problem. In this study, techniques to calculate the Hamiltonian in different hybrid configurations are introduced, and a methodology to look for the initial condition of the co-state is studied, so that the controller is able to realize a desired State Of Charge (SOC) trajectory. To address the issue, we utilize a shooting method with multiple initial conditions based on the concept of the Newton-Raphson method, and all these techniques are realized in a backward looking simulator. The simulation results show that the PMP-based control is a very efficient approach to produce the optimal control trajectory, and the performance is compared to the optimal solution solved by Dynamic Programming (DP).     

Fatigue strength assessment including welding residual stress of spot welded joints subjected to cross-tension loads

This paper presents a method to assess of fatigue strength for resistance spot welded joints, which incorporates welding residual stress effects. To achieve this, first, a non-linear finite element analysis (FEA) was performed to simulate the spot-welding process. To validate the FEA results, the numerically calculated welding residual stresses of spot welds were then compared with experimental results measured by X-ray diffraction method. The residual stress distributions showed good agreement between calculations and experiments. To evaluate the effects of welding residual stress on the fatigue design criterion of resistance spot welded joints subjected to cross-tension load, the stress amplitude (σ_a-res) taking into account welding residual stress at a spot weld was proposed based on a modified Goodman equation incorporating the residual stress effect. Using the stress amplitude σ_a-res at the nugget edge of a spot weld, the ΔP ? N_f relations obtained as the fatigue test results for spot welded joints were systematically rearranged to the σ_a-res ? N_f relation. It was found that the proposed stress amplitude (σ_a-res) provides more reasonable and accurate fatigue design criterion of spot welded joints subjected to cross-tension load.     

Design and optimization of an LPG roller vane pump for suppressing cavitation

A roller vane type liquefied petroleum gas (LPG) pump was developed for a liquid phase LPG injection (LPLi) engine. Most of the LPG pumps used in the current LPLi engines are installed inside of the LPG tank, but this pump is intended to be installed outside of the LPG tank to overcome the difficulty of fixing an in-tank pump. Because LPG has a low boiling point and high vapor pressure, it usually causes cavitation in the pump and consequently deteriorates the flow rate of the pump. The purpose of this work is to optimize the design of the roller vane pump in order to suppress cavitation and increase the fuel flow rate by using a computational fluid dynamics (CFD) analysis. In order to achieve these goals, the intake port configuration and the rotor of the roller vane pump were redesigned and simulated using STAR-CD code. Computation was performed for six different models to obtain the optimized design of the roller vane pump at a constant speed of 2600 rpm and a constant pressure difference between the inlet and outlet of 5 bar. The computation results show that an increased intake port cross-section area can suppress cavitation, and the pump can achieve a higher flow rate when the rotor configuration is changed to increase its chamber volume. When the inlet pressure difference is 0.1 bar higher than the fluid saturation pressure, the pump reaches its maximum flow rate.     

Driver curve speed model and its application to ACC speed control in curved roads

A speed control algorithm for an ACC (Adaptive Cruise Control) system for curved roads is proposed based on driver behavior characteristics. As the foundation of this research, a driver speed model for curved roads is developed using a series of experimental data regarding driver behavior. To adapt the model to each driver’s individual curve speed behavior, the coefficients of the model are identified in real time from the data sequences collected during drivers’ manual operation stage by a self-learning algorithm based on a Recursive Least-Square (RLS) method with a forgetting factor. Using this algorithm, the parameters of the driver model can be identified from the data collected in the manual operation phase, and the identification results are applied during the ACC automatic control phase. Based on the developed model, the ACC speed control algorithm is modified to provide each individual driver with a customized speed profile for the scenario of a curved road with no car ahead. Tests verify the applicability of the modified system.