Predicting WCET of automotive software running on virtual machine monitors

Virtualization is attracting significant interest in the automotive industry because it enables a highly secure and reliable computing environment. More importantly, virtualization maintains the same operating environment for legacy automotive software while exploiting the benefits of widely adopted multicore platforms. To exploit the virtualization technology in an automotive system, it is important to predict the WCET of an automotive application running on a virtual machine monitor (VMM). Unfortunately, the task is challenging because of difficulties in analyzing complicated interactions between a VMM and a guest OS. There are no known attempts to predict the WCET of an application in such an environment. In this paper, we propose a hierarchical and parametric WCET prediction framework. We divide the problem into two subproblems. First, we model the WCET of an application as a function of WCETs of system calls provided by a guest OS. Second, we model WCETs of a system call as a function of WCETs of VMM services. To establish this framework, we clearly identify the places and times of VMM services invoked during the execution of an application. At the time of deployment, the WCET of an application is instantiated by composing the WCET models altogether. We have performed experiments with the proposed framework by predicting the WCETs of sample programs on various virtual and real machine platforms. These experimental results effectively demonstrate the viability of the proposed framework.     

Shape optimization of rubber isolators in automotive cooling modules for the maximization of vibration isolation and fatigue life

Rubber isolators are mounted between a cooling module and a carrier to isolate the car body from vibration due to the rotation of the cooling fan. The isolators should be durable against fatigue loads originating from fan rotation and road disturbance. Thus, the design of rubber isolators is required to maximize both vibration isolation and fatigue life. In this study, the shapes of the rubber isolators are optimally designed using a process integration and design optimization (PIDO) tool that integrates the various computer-aided engineering (CAE) tools necessary for vibration and fatigue analyses, automates the analysis procedure and optimizes the design solution. In this study, we use CAE models correlated to the experimental results. A regression-based sequential approximate optimizer incorporating Process Integration, Automation and Optimization (PIAnO), a commercial PIDO tool, is employed to handle numerically noisy responses with respect to the variation in design variables. Using the analysis and design procedure established in this study, we successfully obtained the optimal shapes of the rubber isolators in two different cooling modules; these shapes clearly have better vibration isolation capability and fatigue lives than those of the baseline designs used in industry.     

Development of control logic for hydraulic active roll control system

Developed in this research is a control logic for the ARC (Active Roll Control) system that uses rotary-type hydraulic stabilizer actuators at the front and rear axles. The hydraulic components of the system were modeled in detail using AMESim, and a driving logic for the hydraulic circuit was constructed based upon the model. The performance of the driving logic was evaluated on a test bench, and it demonstrated good pressure tracking capability. The control logic was then designed with the target of reducing the roll motion of the vehicle during cornering. The control logic consists of two parts: a feedforward controller that generates anti-roll moments in response to the centrifugal force, and a feedback controller that generates anti-roll moments in order to make the roll angle to follow its target value. The developed ARC logic was evaluated on a test vehicle under various driving conditions including a slowly accelerated circular motion and a sinusoidal steering. Through the test, the ARC system demonstrated successful reduction of the roll motion under all conditions, and any discomfort due to the control delay was not observed even at a fast steering maneuver.     

Development of equivalent fuel consumption minimization strategy for hybrid electric vehicles

Power distribution between an internal combustion engine and electric motors is one of main features of hybrid electric vehicles that improves their fuel economy. An equivalent fuel consumption minimization strategy can instantaneously identify the optimal power distribution by converting the battery power into the equivalent fuel power and minimizing the overall fuel consumption. To guarantee the effectiveness of the strategy, it is essential to find the proper value of the conversion factor used to obtain the equivalent fuel power. However, finding the proper value is not a straightforward process because it is necessary to consider the overall power conversion efficiencies and battery charge sustaining strategy for the target driving cycle in advance. In this study, a model-based parameter optimization method is introduced to find the optimal conversion factor. A hybrid electric vehicle simulation model capable of estimating fuel consumption was developed, and the optimal conversion factor was discovered using a genetic algorithm that evaluates its population members using the simulation model. A series of simulations and vehicle tests was conducted to verify the effectiveness of the optimized strategy, and the results show a distinct improvement in fuel economy.     

H8 Control Performance of a Full-Vehicle Suspension Featuring Magnetorheological Dampers

Summary This paper presents an investigation of the feedback control performance of a full-vehicle suspension system featuring magnetorheological (MR) dampers. A cylindrical MR damper is designed and manufactured by incorporating a Bingham model of aMR fluid which is commercially available. After evaluating the field-dependent damping characteristics of the MR damper, a full-vehicle suspension system installed with 4 independent MR dampers is constructed and its governing equations of motion which include vertical, pitch and roll motions are derived. A H 8 controller which has inherent robustness against system uncertainties is formulated by treating the sprung mass of the vehicle as uncertain parameter. This is accomplished by adopting the loop shaping design procedure. For the demonstration of a practical feasibility, control performance characteristics for vibration suppression of the proposed MR suspension system are evaluated under various road conditions through the hardware-in-the-loop simulation (HILS) methodology.     

Fatigue and buckling analysis of automotive components considering forming and welding effects

Some vehicle components are developed by setting target weights to the gram level at their design stages to accomplish a lightweight design. Recently, there have been many studies that have focused on lightweight design through the use of ultra-high-strength steels. However, a lightweight design can face many challenges if the reliability of the analysis is not also secured at the design stage. Such challenges include difficulties in coupled analyses when the file formats are different among PAM-STAMP, ABAQUS, and NASTRAN. In this study, we developed a mapping interface that enables mapping between the file formats of various software programs. Buckling analysis was coupled to the forming analysis, in which pre-strain test data were applied in considering the material’s strain hardening, to evaluate the rigidity of the front lower control arm that controls the wheels and transfers loads. The influence of forming effects on endurance was evaluated, and residual stresses around the weld zone were calculated. A comparison of experimental and analytical results indicated that the proposed analysis was highly reliable.     

Estimation of lateral offset and drift angle for application in secondary collision avoidance system

Recent reports show that the secondary collision on the road gives much higher fatality rate than the other traffic accidents. Many studies have been carried out to prevent the secondary accidents and as a result automotive companies began to introduce brake-based secondary collision avoidance systems. To prevent the secondary accidents it is important to monitor and control the lateral deviation of the vehicle after the primary collision. An estimator for the vehicle’s lateral offset and drift angle based on the in-vehicle sensors and the camera was developed in this paper. By employing sensor fusion scheme and applying extended Kalman filter, the estimator has been designed so that it works even when the camera loses the image of the lanes due to sudden change of the vehicle’s heading angle. For validation of the estimator, simulation has been carried out on various collision scenarios. The simulation results indicated that the estimator of this paper could calculate the vehicle’s lateral deviation with robustness that may be required for application in the secondary collision avoidance systems.     

Estimating vehicle miles traveled (VMT) in urban areas using regression kriging

The recent increase in demand for performance‐driven and outcome‐based transportation planning makes accurate and reliable performance measures essential. Vehicle miles traveled (VMT), the total miles traveled by all vehicles on roadways, has been utilized widely as a proxy for traffic impact assessment, vehicle emissions, gasoline consumption, and crashes. Accordingly, a number of studies estimate VMT using diverse data sources. This study estimates VMT in the urban area of Bucheon, South Korea, by predicting the annual average daily traffic for unmeasured locations using spatial interpolation techniques (i.e., regression kriging and linear regression). The predictive performance of this method is compared with that of the existing Highway Performance Monitoring System (HPMS) method. The results show that regression kriging could provide more accurate VMT estimates than the HPMS method and linear regression, especially with a small sample size. Copyright © 2016 John Wiley & Sons, Ltd.     

GROWTH DIFFERENTIATION FACTOR-5 STIMULATES THE GROWTH AND ANABOLIC METABOLISM OF ARTICULAR CHONDROCYTES

Growthdifferentiationfactor5(GDF5),also knownascartilage derivedmorphogeneticprotein1(CDMP1),isamemberofthebonemorphogenet icprotein(BMP)familywhichbelongstothe transforminggrowthfactorβ(TGFβ)superfami ly[1].GDF5isarelativelynewmemberofthe BMPfamily.LikeotherBMPs,implantationofre combinantGDF5caninduceectopiccartilagefor mationinmusculartissues.Thephysiologicalrole ofGDF5hasbeenreportedincludingregulationof myogenesis,regulationofchondrogenesis,bone morphogenesis,andneurondifferen…     

Robust <Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> preview control of an active suspension system with norm-bounded uncertainties

A robust H _∞ preview control is investigated for an active suspension system with look-ahead sensors. The uncertain system is described by a state-space model with linear nominal parts and additional nonlinear time-varying norm-bounded uncertainties. Proof of robust stability and a feedback-type robust H _∞ preview controller are derived by augmenting the dynamics of the original system and previewed road input. As, however, the augmented previewed road input gives the system a much larger dimension than the original system, much more computation time is required for solving of Riccati equations. To resolve this problem, a decomposed robust H _∞ preview controller is proposed. Robust stability and performance variations for system uncertainties are shown using a numerical example of a quarter-car model.