A forward Markov model for predicting bicycle speed

Transportation - Speed prediction of different transport modes is important in applications such as route planning, transport modelling and energy calculations. In this paper we model bicycle speed...     

Disturbance Observer-Based Sideslip Angle Control for Improving Cornering Characteristics of In-Wheel Motor Electric Vehicles

In this paper, a robust sideslip angle controller based on the direct yaw moment control (DYC) is proposed for in-wheel motor electric vehicles. Many studies have demonstrated that the DYC is one of the effective methods to improve vehicle maneuverability and stability. Previous approaches to achieve the DYC used differential braking and active steering system. Not only that, the conventional control systems were commonly dependent on the feedback of the yaw rate. In contrast to the traditional control schemes, however, this paper proposes a novel approach based on sideslip angle feedback without controlling the yaw rate. This is mainly because if the vehicle sideslip angle is controlled properly, the intended sideslip angle helps the vehicle to pass through the corner even at high speed. On the other hand, the vehicle may become unstable because of the too large sideslip caused by unexpected yaw disturbances and model uncertainties of time-varying parameters. From this aspect, disturbance observer (DOB) is employed to assure robust performance of the controller. The proposed controller was realized in CarSim model described actual electric vehicle and verified through computer simulations.     

New Optimal Power Management Strategy for Series Plug-In Hybrid Electric Vehicles

Recently Plug-in hybrid electric vehicles (PHEVs) have gained increasing attention due to their ability to reduce the fuel consumption and emissions. In this paper a new efficient power management strategy is proposed for a series PHEV. According to the battery state of charge (SOC) and vehicle power requirement, a new rule-based optimal power controller with four different operating modes is designed to improve the fuel economy of the vehicle. Furthermore, the teaching-learning based optimization (TLBO) method is employed to find the optimal engine power and battery power under the specified driving cycle while the fuel consumption is considered as the fitness function. In order to demonstrate the effectiveness of the proposed method, four different driving cycles with various numbers of driving distances for each driving cycle are selected for the simulation study. The performance of the proposed optimal power management strategy is compared with the rule-based power management method. The results verify that the proposed power management method could significantly improve the fuel economy of the series PHEV for different driving conditions.     

Effect of Hydrothermal Aging over a Commercial DOC on NO<Subscript>2</Subscript> Production and Subsequent SCR Efficiency

In this study, the effect of hydrothermal aging over a commercial diesel oxidation catalyst (DOC) on deterioration in nitrogen dioxide (NO₂) production activity has been experimentally investigated based on a micro-reactor DOC experiment. Through this experimental result, the NO₂ to nitrogen oxides (NOx) ratio at DOC outlet has been mathematically expressed as a function of DOC temperature according to various aging conditions. The current study reveals that the catalyst aging temperature is a more dominant factor than the aging duration in terms of the decrease in NO₂ production performance through DOC. The DOC sample hydrothermally aged for 25 h at 750 °C has displayed the lowest NO₂ to NOx ratio compared to the samples aged for 25 ~ 100 h at 650 °C. Also, in this study, the impact of hydrothermal aging of a DOC on the selective catalytic reduction (SCR) efficiency in a ‘DOC + SCR’ aftertreatment system was predicted by using transient SCR simulations. To validate the SCR simulation, this study has conducted a dynamometer test of a non-road heavy-duty diesel engine with employing a commercial ‘DOC + SCR’ system on the exhaust line. The current study has quantitatively estimated the effect of the variation in NO₂ to NOx ratio due to the hydrothermal aging of DOC on the NOx removal efficiency of SCR.     

Detection of Cognitive and Visual Distraction Using Radial Basis Probabilistic Neural Networks

This paper suggests a real-time method for detecting a driver’s cognitive and visual distraction using lateral driving performance measures. The algorithm adopts radial basis probabilistic neural networks (RBPNNs) to construct classification models. In this study, combinations of two driving performance data measures, including the standard deviation of lane position (SDLP) and steering wheel reversal rate (SRR), were considered as measures of distraction. Data for training and testing the RBPNN models were collected under simulated conditions in which fifteen participants drove on a highway. While driving, they were asked to complete auditory recall tasks or arrow search tasks to create cognitively or visually distracted driving periods. As a result, the best performing model could detect distraction with an average accuracy of 78.0 %, which is a relatively high accuracy in the human factors domain. The results demonstrated that the RBPNN model using SDLP and SRR could be an effective distraction detector with easy-to-obtain and inexpensive inputs.     

Feature-Based Cad System Buildup for Passenger Airbag Design

The passenger airbag (PAB) requires a large volume and fast deployment because of the large distance between the dashboard and the passenger. And various shapes and sizes of the PAB are required depending on the type of vehicle. However, since the PAB modeling process for each design change is complicated and time consuming, the design parameters of the PAB could not be well investigated. In this study, a unique feature-based CAD system has been proposed that easily constructs PAB CAD model and then generates PAB FE model for collision analysis. Main keypoints and widths of PAB that determine the shape and size have been extracted by analyzing the geometric-feature of airbag. The PAB CAD model can be easily constructed by inputting keypoints and widths information. Then, from the constructed PAB CAD model, the PAB FE model is automatically generated. Finally, the generated PAB FE model can be directly employed for collision analysis, thereby reducing the modeling time of the PAB and enabling efficient parametric studies on design.     

Effects of Residual Ash on Dpf Capture and Regeneration

To study the effects of residual ash on the capture and regeneration of a diesel particulate filter (DPF), repeated capture and complete regeneration experiments were conducted. An engine exhaust particulate sizer was used to measure the particle size distribution of diesel in the front and back of DPF. Discrepancies in the size distribution of the particulate matter in repeated trapping tests were analyzed. To achieve complete DPF regeneration, a DPF regeneration system using nonthermal plasma technology was established. The regeneration carbon removal mass and peak temperatures of DPF internal measuring points were monitored to evaluate the effect of regeneration. The mechanism explaining the influence of residual ash on DPF capture and regeneration was thoroughly investigated. Results indicate that the DPF trapping efficiencies of the nuclear-mode particles and ultrafine particles have significant improvements with the increase quantity of residual ash, from 90 % and 96.01 % to 94.17 % and 97.27 %, respectively. The exhaust backpressure of the DPF rises from 9.41 kPa to 11.24 kPa. Heat transfer in the DPF is improved with ash, and the peak temperatures of the measuring points accordingly increase. By comparing the regeneration trials, the elapsed time for complete regeneration and time difference for reaching the peak temperature between adjacent reaction interfaces are extended with increased quantity of ash. The carbon removal mass rises by 34.00 %.     

Influence of the geometric parameters of the vehicle frontal profile on the pedestrian’s head accelerations in case of accidents

The goal of this paper is to determine how the geometry of the vehicle’s frontal profile is influencing the pedestrian’s head accelerations (linear and angular) in car-to-pedestrian accidents. In order to achieve this goal, a virtual multibody dummy of the pedestrian was developed and multiple simulations of accidents were performed using vehicles with different frontal profile geometry, from different classes. The type of accidents considered is characteristic for urban areas and occur at relatively low speed (around 30 km/h) when an adult pedestrian is struck from the rear and the head acceleration variation are the measurement of the accident severity. In the accident simulation 3D meshes were applied on the geometry of the vehicles, in order to define the contact surface with the virtual dummy, similar with real vehicles. The validation of the virtual pedestrian dummy was made by performing two crash-tests with a real dummy, using the same conditions as in the simulations. The measured accelerations in the tests were the linear and angular accelerations of the head during the impact, and these were compared with the ones from the simulations. After validating the virtual model of the car-to-pedestrian accident, we were able to perform multiple simulations with different vehicle shapes. These simulations are revealing how the geometric parameters of the vehicle’s frontal profile are influencing the head acceleration. This paper highlights the main geometric parameters of the frontal profile design that influence the head injury severity and the way that the vehicles can be improved by modifying these parameters. The paper presents an approach to determine the “friendliness” of the vehicle’s frontal profile in the car-to-pedestrian collision.     

Tire wear estimation based on nonlinear lateral dynamic of multi-axle steering vehicle

This paper presents a novel nonlinear dynamic model of a multi-axle steering vehicle to estimate the lateral wear amount of tires. Firstly, a 3DOF nonlinear vehicle dynamic model is developed, including dynamic models of the hydropneumatic suspension, tire, steering system and toe angle. The tire lateral wear model is then built and integrated into the developed vehicle model. Based on the comparison of experimental and simulation results, the nonlinear model is proved to be better than a linear model for the tire wear calculation. In addition, the effects of different initial toe angles on tire wear are analyzed. As simulation results shown, the impact of the dynamic toe angle on the tire wear is significant. The tire wear amount will be much larger than that caused by normal wear if the initial toe angle increases to 1° - 1.5°. The results also suggest that the proposed nonlinear model is of great importance in the design and optimazation of vehicle parameters in order to reduce the tire wear.     

Schlieren,Shadowgraph, Mie-scattering visualization of diesel and gasoline sprays in high pressure/high temperature chamber under GDCI engine low load condition

Three visualization methods, Schlieren, Shadowgraph, and Mie-scattering, were applied to compare diesel and gasoline spray structures in a constant volume chamber. Fuels were injected into a high pressure/high temperature chamber under the same in-cylinder pressure and temperature conditions of low load in a GDCI (gasoline direct injection compression ignition) engine. Two injection pressures (40 MPa and 80 MPa), two ambient pressures (4.2 MPa and 1.7 MPa), and two ambient temperatures (908 K and 677 K) were use. The images from the different methods were overlapped to show liquid and vapor phases more clearly. Vapor developments of the two fuels were similar; however, different liquid developments were seen. At the same injection pressure and ambient temperature, gasoline liquid propagated more quickly and disappeared more rapidly than diesel liquid phase. At the low ambient temperature and pressure condition, gasoline and diesel sprays with higher injection pressures showed longer liquid lengths due to higher spray momentum. At the higher ambient temperature condition, the gasoline liquid length was shorter for the higher injection pressure. Higher volatility of gasoline is the main reason for this shorter liquid length under higher injection pressure and higher ambient temperature conditions. For a design of GDCI engine, it is necessary to understand the higher volatility of gasoline.