Validity and limitations of the kinematic roll center concept from the viewpoint of spatial kinematics using screw theory

In this research, the concept of the kinematic roll center is reviewed from the viewpoint of three-dimensional spatial kinematics. The theory of screws, which is widely used in spatial kinematics and robotics, is used to prove the validity of the conventional planar methods for finding the roll center in an initial symmetric vehicle position. The kinematic roll axis, which is referred to as the roll twist axis in this paper, is defined as the instantaneous screw axis of the vehicle body in roll motion with respect to the ground, and a three-dimensional method to determine the roll twist axis of a full-vehicle model in an initial symmetric position is introduced. The proposed method is based on screw theory, which relates the kinematics of a full-vehicle model to the statics of the full-vehicle model using the concepts of screws, twists, wrenches, the rate of working, and the reciprocity of screws. The results of the proposed three-dimensional method are compared with those of the conventional planar methods, and it is found that the conventional methods are valid under the assumption that the vehicle is in a symmetric situation.     

Design and evaluation of sideslip angle observer for vehicle stability control

This paper presents a method for estimating the vehicle side slip angle, which is considered as a significant signal in determining the vehicle stability region in vehicle stability control systems. The proposed method combines the model-based method and kinematics-based method. Side forces of the front and rear axles are provided as a weighted sum of directly calculated values from a lateral acceleration sensor and a yaw rate sensor and from a tire model according to the nonlinear factor, which is defined to identify the degree of nonlinearity of the vehicle state. Then, the side forces are fed to the extended Kalman filter, which is designed based on the single-track vehicle model associated with a tire model. The cornering stiffness identifier is introduced to compensate for tire force nonlinearities. A fuzzy-logic procedure is implemented to determine the nonlinear factor from the input variables: yaw rate deviation from the reference value and lateral acceleration. The proposed observer is compared with a model-based method and kinematics-based method. An 8 DOF vehicle model and Dugoff tire model are employed to simulate the vehicle state in MATLAB/SIMULINK. The simulation results shows that the proposed method is more accurate than the model-based method and kinematics-based method when the vehicle is subjected to severe maneuvers under different road conditions.     

Computational study of charge stratification in early-injection SCCI engines under light-load conditions

Under light-load conditions in early-injection stratified-charge compression-ignition (SCCI) engines, excessive premixing can lead to undesirable levels of unburned hydrocarbons (UHC) and carbon monoxide (CO) emissions. Optimal stratification can reduce these emissions. In this work, the effects of changes in swirl, injection pressure, injector hole-size and number of holes, injection timing, and piston geometry on stratification are computationally investigated. It is shown that these parameters affect the stratification through their influence on the rate of spray penetration, drop vaporization, and fuel/air mixing. The outcome is characterized by examining the evolution of the spatial distribution of the fuel vapor in the chamber and its mass-based distribution function. All other parameters remaining the same, decreasing drop size leads to faster vaporization and richer mixtures. Increasing penetration leads to greater spreading and leaner mixtures. Increasing spray included-angle leads to greater spreading and leaner mixtures. Increasing injection pressure leads to increased mixing and leaner mixtures. Increasing injector hole-size leads to richer mixtures at lighter loads because the duration of injection is reduced and the fuel is confined closer to the axis. Increasing swirl leads to faster breakup of the head-vortex and confinement of the fuel closer to the axis, and hence richer mixture.     

Engine clutch torque estimation for parallel-type hybrid electric vehicles

This paper mainly focuses on the accurate estimation of the torque transferred through the engine clutch installed between the engine and the drive motor in parallel-type hybrid electric vehicles. The estimation of the engine clutch torque primarily relies on the forward-direction observer which uses the nominal engine net torque information. To overcome the limitation of using the nominal engine torque information that it may not be accurate during the transient states or due to the influence of external disturbance such as the road condition and wind, the forward-direction observer is supplemented by the use of reverse-direction observer which uses the driveline model and wheel speed measurements. In addition, the drive motor torque information is used to calibrate the nominal engine torque during the idle charging state, so that the driveline characteristic unique to parallel-type hybrid electric vehicle can be utilized to increase the estimation accuracy. Finally, the estimation performance of the designed observer is tested via simulation and experiments based on a real vehicle.     

In-depth understanding of lane changing interactions for in-vehicle driving assistance systems

Lane-changing events are often related with safety concern and traffic operational efficiency due to complex interactions with neighboring vehicles. In particular, lane changes in stop-and-go traffic conditions are of keen interest because these events lead to higher risk of crash occurrence caused by more frequent and abrupt vehicle acceleration and deceleration. From these perspectives, in-depth understanding of lane changes would be of keen interest in developing in-vehicle driving assistance systems. The purpose of this study is to analyze vehicle interactions using vehicle trajectories and to identify factors affecting lane changes with stop-and-go traffic conditions. This study used vehicle trajectory data obtained from a segment of the US-101 freeway in Southern California, as a part of the Next Generation Simulation (NGSIM) project. Vehicle trajectories were divided into two groups; with stop-and-go and without stop-and-go traffic conditions. Binary logistic regression (BLR), a well-known technique for dealing with the binary choice condition, was adopted to establish lane-changing decision models. Regarding lane changes without stop-and-go traffic conditions, it was identified based on the odd ratio investigation that he subject vehicle driver is more likely to pay attention to the movement of vehicles ahead, regardless of vehicle positions such as current and target lanes. On the other hand, the subject vehicle driver in stop-and-go traffic conditions is more likely to be affected by vehicles traveling on the target lane when deciding lane changes. The two BLR models are adequate for lane-changing decisions in normal and stop-and-go traffic conditions with about 80 % accuracy. A possible reason for this finding is that the subject vehicle driver has a tendency to pay greater attention to avoiding sideswipe or rear-end collision with vehicles on the target lane. These findings are expected to be used for better understanding of driver’s lane changing behavior associated with congested stop-and-go traffic conditions, and give valuable insights in developing algorithms to process sensor data in designing safer lateral maneuvering assistance systems, which include, for example, blind spot detection systems (BSDS) and lane keeping assistance systems (LKAS).     

Lane assignment problem using a genetic algorithm in the Automated Highway Systems

This paper deals with the lane assignment problem in the Automated Highway Systems (AHS). The purpose of lane assignment strategies is to increase throughput on multi-lane highways with many entry and exit points, based on the itineraries of vehicles using the highway (point of entry, time of entry and exit point) and the effects of maneuvers. Using partitioned lane assignment strategies, the lane assignment problem is formulated as an optimization problem to find the proper positions of partitions. Then the optimal problem is solved using a Genetic Algorithm (GA). The proposed algorithm has been validated by comparing its solution with that of an all-cases algorithm for a simple case. Moreover, a traffic simulator with a realistic car-following model as well as lane change logic has been developed. The simulation results show the efficiency of the proposed genetic algorithm, compared with random assignment algorithms.     

Measurement of hydrocarbon and carbon monoxide emissions during the starting of automotive DI Diesel engines

Most of hydrocarbon (HC) and carbon monoxide (CO) emissions from automotive DI Diesel engines are produced during the engine warm-up period and are primarily caused by difficulties in obtaining stable and efficient combustion under these conditions. Furthermore, the contribution of engine starting to these emissions is not negligible; since this operating condition is highly unfavorable for the combustion progress. Additionally, the catalytic converter is ineffective due to the low engine temperature. In conjunction with adequate engine settings (fuel injection and fresh air control), either the glow plugs or the intake air heater are activated during a portion of the engine warm-up period, so that a nominal engine temperatures is reached faster, and the impact of these difficulties is minimized. Measurement of gaseous pollutants during engine warm-up is currently possible with detectors used in standard exhaust gas analyzers (EGA), which have response times well-suited for sampling at such transient conditions. However, these devices are not suitable for the measurement of exhaust emissions produced during extremely short time intervals, such as engine starting. Herein, we present a methodology for the measurement of the cumulative pollutant emissions during the starting phase of passenger car DI Diesel engines, with the goal of overcoming this limitation by taking advantage of standard detectors. In the proposed method, a warm canister is filled with an exhaust gas sample at constant volumetric flow, during a time period that depends on the engine starting time; the gas concentration in the canister is later evaluated with a standard EGA. When compared with direct pollutant measurements performed with a state-of-art EGA, the proposed procedure was found to be more sensitive to combustion changes and provided more reliable data.     

Analysis of disc brake instability due to friction-induced vibration using a distributed parameter model

This paper deals with friction-induced vibration of a disc brake system with a constant friction coefficient. A linear, lumped, and distributed parameter model to represent the floating caliper disc brake system is proposed. The complex eigenvalues are used to investigate the dynamic stability, and, in order to verify simulations which are based on the theoretical model, an experimental modal test and dynamometer test are performed. The comparison of experimental and theoretical results shows good agreement, and the analysis indicates that modal coupling due to friction forces is responsible for disc brake squeal. Also, squeal type instability is investigated, using a parametric analysis. This indicates which parameters have influence on the propensity of brake squealing. This is helpful for validating the analysis model and establishing confidence in the experimental results of the modified system. These results may also be useful during system development or diagnostic analysis.     

New nonlinear bushing model for general excitations using Bouc-Wen hysteretic model

Because the characteristics of rubber bushing significantly affect the accuracy of vehicle dynamics simulations, they should be accurately modeled in the vehicle suspension model. In this paper, a new nonlinear bushing model for automotive bushing components is developed to improve the accuracy of vehicle dynamics analysis. Bushing components were first tested to capture the nonlinear and hysteretic behavior of typical elements by using a MTS 3-axis elastomer tester. A simple Bouc-Wen hysteretic differential model was modified to generate a more precise rubber bushing model. A sine wave, step input, and random excitations are imposed on the bushing. The ADAMS program is used to calculate sensitivity and the VisualDOC program is employed to find the optimal parameters for the bushing model. An error function is designed to find optimal parameters of the model. Parameter identification is carried out to satisfy the static and dynamic characteristics due to sine and step excitation inputs. It was proved that the proposed model could predict the bushing forces under sine, step, and random inputs well. The errors are within 10% in the overall range. To show the validity of the proposed model, a numerical example was also carried out. Because the bushing forces due to random excitation input show good agreement with experiments, the proposed bushing model is available in the vehicle dynamics simulation.     

Excitation force analysis of a powertrain based on CAE technology

The excitation force of a powertrain is one of major sources of interior noise in a vehicle. This paper presents a novel approach to predict the interior noise caused by the vibration of the powertrain by using the hybrid TPA (transfer path analysis) method. Although the traditional transfer path analysis (TPA) is useful for the identification of powertrain noise sources, it is difficult to modify the structure of a powertrain by using experiments for the reduction of vibration and noise. In order to solve this problem, the vibration of the powertrain in a vehicle is numerically analyzed by using the finite element method (FEM). The vibration of the other parts of the vehicle is investigated by using experiments based on vibrato-acoustic transfer function (VATF) analysis. These two methods are combined for the prediction of interior noise caused by a powertrain. Throughout this research, two papers are presented. This paper presents a simulation of the excitation force of the powertrain exciting the vehicle body based on numerical simulation. The other paper presents a prediction of interior noise based on the hybrid TPA, which uses the VATF of the car body and the excitation force predicted in this paper.