Development of route information based driving control algorithm for a range-extended electric vehicle

A route information based driving control algorithm was developed for an RE-EV which consists of two motorgenerators, MG1 and MG2. A threshold power which controls the engine on/off to charge the battery was obtained by an optimization process using route information, such as the vehicle velocity and altitude. The threshold power allows the vehicle to travel to the final destination while making the final battery SOC close to SOC _low. Using the threshold power, route based control (RBC) was proposed by considering the driver’s characteristics and traffic conditions using the driving data base. In addition, a relationship between the threshold power and various initial battery SOC was obtained by off-line optimization. The performance of the RBC was evaluated by simulation and human-in-the-loop simulation (HILS) for city driving. It was found from the simulation and HILS results that the RBC achieved approximately 4 % to 12 % reduction in fuel consumption compared to the existing charge depleting/charge sustaining (CD/CS) driving control.     

SiMoCo: the viability of a prototype platform for a coastal monitoring system: a case study

Coastal zones are among the most productive areas in the world, offering a wide variety of valuable habitats and ecosystems services. Despite the low population density in the Brazilian coastal zone, their distribution is quite concentrated near some coastal cities and state capitals. This concentration places enormous pressure on coastal resources. Therefore, the main objective of this paper is to present an overview on the current status of SiMoCo (Sistema de Monitoramento Costeiro, or Coastal Monitoring System in English) project as a possible early warning system that can be integrated to the Brazilian Coastal Management Information System. This prototype platform provides a real-time access to the composition, organization and simulation of planktonic communities. First, our results demonstrate such a system detecting a target dinoflagellate; second, we apply structural and functional indexes to compare and characterize the ecological networks from two different coastal areas. Conclusions are made about SiMoCo’s feasibility and its possible contribution to the decision-making process within integrated coastal zone management (ICZM) strategies.     

Vehicle stability control system for enhancing steerabilty,lateral stability,and roll stability

The Vehicle stability control system is an active safety system designed to prevent accidents from occurring and to stabilize dynamic maneuvers of a vehicle by generating an artificial yaw moment using differential brakes. In this paper, in order to enhance vehicle steerability, lateral stability, and roll stability, each reference yaw rate is designed and combined into a target yaw rate depending on the driving situation. A yaw rate controller is designed to track the target yaw rate based on sliding mode control theory. To generate the total yaw moment required from the proposed yaw rate controller, each brake pressure is properly distributed with effective control wheel decision. Estimators are developed to identify the roll angle and body sideslip angle of a vehicle based on the simplified roll dynamics model and parameter adaptation approach. The performance of the proposed vehicle stability control system and estimation algorithms is verified with simulation results and experimental results.     

Effect of structural variables on automotive body bumper impact beam

Increasing fuel economy has been a central issue in the development of new cars, and one of the important strategies to improve fuel economy is to decrease vehicle weight. In order to obtain this goal, researchers have sought to make bumpers lighter without sacrificing strength, ability to absorb impact, or passenger safety. In this study, the effects of structural variables on the torsional stiffness of a body bumper impact beam were analyzed for possible weight reduction. To this end, the effects of variation of section height, increase of impact beam thickness and the addition of stays in a bumper impact beam were carefully investigated and compared. Among these, the most effective way to increase the torsional stiffness of the bumper impact beam was found to be increasing the section height. In addition, the potential for overall weight reduction of the impact beam was examined by comparing the crash capability of a bumper using conventional steels with that of high-strength steel (boron steel) with a tensile strength of 1.5 GPa. This analysis could serve as a guide to design for optimal bumper impact beam development.     

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.     

Fatigue design approach for the spot-welded T-type member using a simulated single spot-welded joint

In order to develop a fatigue design method for actual railroad car and commercial vehicle body structures using the fatigue data of simulated single spot-welded lap joints, we first analyzed the stress distribution and evaluated fatigue strength of spot-welded T-type members that are the components of actual railroad car and commercial vehicle body structures. Next, fatigue design approach of these members using the fatigue data of single spot-welded lap joints was investigated. From our results, we found that, even though there was a quantitative difference of fatigue strength between the single spot-welded joint and the actual members over the same number of fatigue cycles, through the use of appropriate correction, the fatigue design criterion of actual spot-welded members, such as those used in railroad car and commercial vehicle body, can be predicted using the fatigue strength of single spot-welded joint.     

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.     

Robustness analysis of ESC ECU to characteristic variation of vehicle chassis components using HILS technique

The ESC system, since its introduction in the mid 90s, has greatly contributed to prevention of vehicle accidents with its capability of maintaining vehicle stability in severe driving conditions. Due to its significant advantages, many nations are now adopting regulations that mandate installation of the ESC system in all classes of passenger vehicles — from mini to luxury. Accordingly it became important to know whether an ESC ECU can yield good performance on a wide range of vehicle parameter changes. In this paper, robustness analysis was conducted to study how characteristic variation of the main chassis components affect the performance of the ESC ECU. This analysis was carried out using a HILS system built on an actual ESC ECU. The variation range of each chassis component was carefully selected considering the component’s design criteria adopted in automotive industries. Based upon the robustness analysis results, the allowable variation ranges of the chassis components for ensuring sound performance of an ESC ECU were proposed.     

Development of an autonomous braking system using the predicted stopping distance

An autonomous braking system is designed using the prediction of the stopping distance. The stopping distance needs to be determined by considering several factors such as the desired deceleration and the speed of the hydraulic brake actuator. In particular, the actuator speed is very critical because it affects the shape of the deceleration response and it determines the accuracy of the predicted stopping distance. The autonomous braking control algorithm is designed based on the predicted stopping distance. The proposed autonomous braking system has been validated in autonomous vehicle tests and demonstrates that the subject vehicle can avoid the collision effectively.     

Experimental approach to developing human driver models considering driver’s human factors

A new approach to develop human driver models (HDMs) is proposed in accordance with the drivers’ generic human factors, i.e., gender, age, and experience, to develop more realistic vehicle simulations. The HDMs consist of three independent and stepwise models with functioning driver’s information processing stages based on the human factors: constructing drivers’ preview distance (PVD) models as a ‘cognition process’, implementing a finite preview optimal control algorithm as a ‘decision process’, and differentiating an ‘operation process’ according to neuromuscular efficiency. Eight different groups of 65 drivers with a 2 × 2 × 2 within-subject design participated in both the PVD estimates and neuromuscular efficiency tests to develop a set of statistically different HDMs. Regarding the preview distance models, an analysis of covariance (ANCOVA) procedure was adopted with two covariates (i.e., vehicle velocity and road curvature), while analyses of variance (ANOVAs) were performed on the neuromuscular efficiency parameters. The ANCOVA procedure produced eight significantly different cognition processes, whereas the ANOVAs revealed gender differences for the drivers’ neuromuscular systems. Moreover, an integrated vehicle simulation was configured with the HDMs using Carsim and Simulink software to observe the differential effects of both the cognition and operation processes on a double-lane-change (DLC) maneuver. During the simulations, gender differences in real-world DLC tests were also identified, especially between the male-oldexpert and the female-young-novice HDMs. The results presented in this study suggest that differentiating HDMs according to human factors is an essential process when utilizing vehicle simulations in the early stage of developing an intelligent vehicle system.