Cooling performance evaluation of height-downsized front end module for pedestrian protection

The front end module (FEM) needs enough space from hood to absorb the energy from any pedestrian collision. The FEM with downsized cooling module for pedestrian protection is important to reduce the severity of pedestrian injury. When a vehicle collision happens, the FEM with downsized cooling module is required to reduce the risk of injury to the upper legs of adults and the heads of children. In this study, the performance of cooling module to cool the engine was investigated under 25% height reduction. The heat dissipation and pressure drop characteristics have been experimentally studied with the variation of coolant flow rate, air inlet velocity and A/C operation (on/off) for the downsized cooling module. The results indicated that the cooling performance was about 94% level compared to that of the conventional cooling module. Therefore, we concluded that the cooling module had a good performance, and expected that the cooling module could meet the same cooling performance as conventional cooling module through optimization of components efficiency. This paper also deals with the development of FEM with downsized cooling module for the cooling performance level in vehicles. In the test of front end module??s heat dissipation performance, the prototype presented about 15% decrease under the conditions of all the vehicle speeds than that of conventional one.     

Simulation of a powertrain system for the diesel hybrid electric bus

The plug-in hybrid electric bus (HEB) is designed to overcome the vulnerable driving range and performance limitations of a purely electric vehicle (EV) and have an improved fuel economy and lower exhaust emissions than those of a conventional bus and convention HEBs. The control strategy of the plug-in parallel HEB??s complicated connected propulsion system is one of the most significant factors for achieving a higher fuel economy and lower exhaust emissions than those of the HEV. The proposed powertrain control strategy has flexibility in adapting to the battery??s state of charge (SOC), exhaust emissions, classified driving patterns, driving conditions, and engine temperature. Simulation is required to model hybrid powertrain systems and test and develop powertrain control strategies for the plug-in parallel HEB. This paper describes the simulation analysis tools, powertrain components?? models and modifications, simulation procedure, and simulation results.     

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.     

Smooth motion control of the adaptive cruise control system by a virtual lead vehicle

The adaptive cruise control system maintains the appropriate distance to the lead vehicle when the lead vehicle exists and maintains the desired speed when no lead vehicle is detected. A virtual lead vehicle scheme is introduced to make the switching between the speed control algorithm and the distance control algorithm unnecessary and simplify the structure of the control system. The speed and the position of the virtual vehicle can be decided by the control system according to the current situation. Smoother responses are achieved by the virtual lead vehicle scheme compared to the conventional mode switching scheme. This method is also shown to provide a good reaction for when a lead vehicle cuts in or out. A linear quadratic controller with variable weights is suggested to control the virtual lead vehicle. This scheme shows improved performance in terms of passenger comfort and fuel efficiency of the host vehicle.     

Numerical modeling of journal bearing considering both elastohydrodynamic lubrication and multi-flexible-body dynamics

This study uses an elastohydrodynamic lubrication model coupled with multi-flexible-body dynamics (MFBD) to analyze dynamic bearing lubrication characteristics, such as pressure distribution and oil film thickness. To solve the coupled fluid-structure interaction system, this study uses an MFBD solver and an elastohydrodynamics module. The elastohydrodynamics module passes its force and torque data to the MFBD solver, which can solve general dynamic systems that include rigid and flexible bodies, joints, forces, and contact elements. The MFBD solver analyzes the positions, velocities, and accelerations of the multi-flexible-body system while incorporating the pressure distribution results of the elastohydrodynamics module. The MFBD solver then passes the position and velocity information back to the elastohydrodynamics solver, which reanalyzes the force, torque, and pressure distribution. This iteration is continued throughout the analysis time period. Other functions, such as mesh grid control and oil hole and groove effects, are also implemented. Numerical examples for bearing lubrication systems are demonstrated.     

Expanding transmission capacity of can systems using dual communication channels with kalman prediction

The controller area network (CAN) protocol is widely used for in-vehicle network (IVN) systems, and many automotive companies also use the CAN in chassis network systems. However, the increasing number of electronic control units (ECUs) dictated by the need for more intelligent and fuel-efficient functions requires an IVN system with a greater transmission capacity and less network delay. Automotive companies have tried several approaches such as segmenting CAN systems and developing time-triggered protocols. This paper presents a practical method for increasing the transmission capacity and reducing the network delay in CAN systems using dual communication channels with a traffic-balancing algorithm based on Kalman prediction to forecast the traffic on each channel and allocate frames to the one that is most appropriate. An experimental testbed using commercial microcontrollers with two or more CAN protocol controllers was used to demonstrate the feasibility of the Kalman traffic-balancing algorithm. Experimental results show that the traffic-balancing CAN system with Kalman prediction reduced the transmission delay of all priority messages compared to that of a simple method, such as a channel-switching CAN, without sacrificing the performance for high-priority messages.     

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.     

Technology analysis and low-cost design of automotive radar for adaptive cruise control system

Recently, the advanced driver assistance system (ADAS), which helps mitigate car accidents, has been developed using environmental detection sensors, such as long and short range radar, lidar, wide dynamic range cameras, ultrasonic sensors and laser scanners. Among these detection sensors, radars can quickly provide drivers with reliable information about the velocity, distance and direction of a target obstacle, as well as information about the vehicle in changing weather conditions. In the adaptive cruise control system (ACCS), three radar sensors are usually needed because two short range radars are used to detect objects in the adjacent lane and one long range radar is used to detect objects in-path. In this paper, low-cost radar based on a single sensor, which can detect objects in both the adjacent lane and in-path, is proposed for use in the ACCS. Before designing the proposed radar, we analyzed the world-wide radar technology and market trends for ACCS. Based on this analysis, we designed a novel radar sensor for the ACCS using radar components, such as an antenna, transceiver module, transceiver control module and signal processing algorithm. Finally, target detection experiments were conducted. In the experimental results, the proposed single radar can successfully complete the detection required for the ACCS. In the conclusion, the perspective and issues in the future development of the ACCS radar are described.     

Prediction of ambient carbon monoxide concentration using nonlinear time series analysis technique

This study evaluates the potential of nonlinear time series analysis based methods in predicting the carbon monoxide concentration in an urban area. To establish the functional relationship between current and future observations, two models based on local approximations and neural network approximations are used. To compare the performance of the models, an autoregressive integrated moving average model is also applied. The multi-step forecasting capabilities of the models are evaluated.