Design and simuation of a vehicle test bed based on intelligent transport systems

As growing demand of vehicle safety system, especially regarding intelligent transport systems (ITS), automotive manufacturers are focusing more on driving safety and efficient transportation for vehicle users. Many safety systems have been launched in the market recently so, it is important to evaluate the vehicle safety systems and ITS. The ITS based intelligent vehicle test bed was constructed to meet the growing demand of test and verification for such ADAS and ITS systems. First, this paper describes in detail concept of the test-bed. This test-bed is carefully designed to meet the requirements of ISO/TC204 standards. In order to verify the design of the test-bed, virtual test with driving siulator was processed on a virtual test tracks. This test-bed will be used to conduct testing on various ITS and ADAS technologies, such as adaptive cruise control (ACC), lane departure warning system (LDWS), cooperative intersection warning system as well as rollover stability control (RSC) and electronic stability control (ESC), etc.     

Shape design optimization of interior permanent magnet motor for vibration mitigation using level set method

This paper presents a new optimization method to obtain the structural design of permanent magnet motor which can reduce the mechanical vibration. The optimization problem is formulated to minimize a multi-objective function including the mean compliance of the whole stator for maximizing the stiffness under the magnetic force and the torque ripple by aligning torque profiles to a constant target value for maximizing the magnetic performance, with constraint for material usage. The level set function is introduced for representing the structural boundaries and calculating the material properties. A coupled magneto-mechanical analysis is performed to verify the vibration characteristic of the motor system and obtain the design sensitivities. To confirm the usefulness of the proposed design method and to obtain the optimum structural design for low vibration motor, a design example of 20 kW interior permanent magnet motor developed for the power train of a hybrid electric vehicle is provided.     

Novel large scale simulation process to support dot’s cafe modeling system

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation’s (DOT’s) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT’s National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the “Volpe model” or the “CAFE model”), which was developed by DOT’s Volpe National Transportation Systems Center for the 2005–2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees”. Part of the model’s function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry’s standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies.     

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.     

Improving multi-channel wave-based V2X communication to support advanced driver assistance system (ADAS)

The advent of vehicle-to-everything (V2X) communication has opened the opportunity to design advanced driver assistance systems (ADAS) that collect information from sensors in neighboring vehicles and roadside infrastructure. IEEE and ETSI have designed network protocol standards for V2X communications. Despite the differences between the vehicular wireless communication architecture defined by ETSI and the IEEE protocol stack, the two standards have multichannel operations as a main commonality, with some channels dedicated to safety-critical applications and others to nonsafety services. Some recent studies have demonstrated that these standards might not provide sufficient channel utilization for reliable exchange of information in mid- and heavily congested scenarios. In this paper, we propose and evaluate the performance of a driver-assistance system to reduce the connectivity gaps between vehicles and roadside units (RSUs). This cooperative system of multi-service channel allocation will improve radio channel utilization. We also show that the required latency for this inter-vehicle communication can be obtained using the IEEE-WAVE standards and dedicated short-range communication (DSRC) proposed for vehicular environments. Simulation results show that the proposed scheme can improve the average throughput by up to 15 % in various traffic density conditions compared with the dynamic channel allocation method.     

Kriging assisted on-line torque calculation for brushless DC motors used in electric vehicles

Torque is one of the most important control factors for a vehicle’s motion. Compared with internal combustion engines, electric motors can have a more accurate torque feedback which brings a lot of advantages to vehicle dynamics and stability control. However, motors used in electric vehicles are facing more difficult conditions than those in conventional applications, such as extreme high/low temperature changing, vibration, aging, etc. The variation of motor parameters due to harsh working conditions can lead to serious problems for motor torque estimation and thus dynamic control of electric vehicles. In this paper, a new method using kriging to estimate the back EMF and thus accurately calculate motor torque in an on-line fashion is presented. With motor speed and rotor position as inputs, kriging predicts back EMF as the output that is used to calculate the motor torque with three phase currents. Using this novel method, motor torque can be accurately calculated even facing high/low temperatures or aging conditions. Experimental tests under the high temperature have been conducted to verify the applicability of the proposed method.     

Non-intrusive polynomial chaos for efficient uncertainty analysis in parametric roll simulations

Monte Carlo analyses are generally considered the standard for uncertainty analysis. While accurate, these analyses can be expensive computationally. Recently, polynomial chaos has been proposed as an alternative approach to the estimation of uncertainty distributions (Hosder et al. A non-intrusive polynomial chaos method for uncertainty propagation in CFD simulations. In: 44th AIAA aerospace sciences meeting and exhibit, Reno, Nevada, 2006; Wu et al. Uncertainty analysis for parametric roll using non-intrusive polynomial chaos. In: Proceedings of the 12th international ship stability workshop, Washington, DC, USA, 2011). This approach works by representing the function as a series of orthogonal polynomials; the weights for which can be calculated via several methods. Previous studies have demonstrated the usefulness of this technique for comparatively simple systems such as parametric roll modeled by the Mathieu equation with normally distributed parameter values (Wu et al. Uncertainty analysis for parametric roll using non-intrusive polynomial chaos. In: Proceedings of the 12th international ship stability workshop, Washington, DC, USA, 2011). In the present work, a polynomial chaos method is applied to a nonlinear computational ship dynamics model with normally distributed input parameters. Test cases were selected where parametric roll was expected to potentially occur. The resulting probability distributions are compared to the results of a Monte Carlo analysis. In general, these results demonstrate good agreement between Monte Carlo simulation and polynomial chaos in the absence of capsize with significant computation gains found with polynomial chaos. Overall, we conclude that polynomial chaos is an effective tool for reducing simulation time costs when studying parametric roll, and potentially other ship dynamics phenomena, particularly in the absence of capsize-like bifurcations.     

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.     

现代信息技术在桥梁结构无损检测中的应用

桥梁结构无损检测与评估技术的研究是当前国际上土木工程领域的难点和热点。文章结合信息技术发展的特点,探讨和总结了现代信息技术在桥梁结构无损检测与评估上的应用与发展,并对相关问题进行了讨论。     

How do people respond to congestion mitigation policies? A multivariate probit model of the individual consideration of three travel-related strategy bundles

This study explores the relationships between adoption and consideration of three travel-related strategy bundles (travel maintaining/increasing, travel reducing, and major location/lifestyle change), linking them to a variety of explanatory variables. The data for this study are the responses to a fourteen-page survey returned by nearly 1,300 commuting workers living in three distinct San Francisco Bay area neighborhoods in May 1998. We first identified patterns of adoption and consideration among the bundles, using pairwise correlation tests. The test results indicate that those who have adopted coping strategies continue to seek for improvements across the spectrum of generalized cost, but perhaps most often repeating the consideration of a previously-adopted bundle. Furthermore, we developed a multivariate probit model for individuals’ simultaneous consideration of the three bundles. It is found that in addition to the previous adoption of the bundles, qualitative and quantitative Mobility-related variables, Travel Attitudes, Personality, Lifestyle, Travel Liking, and Sociodemographics significantly affect individual consideration of the strategy bundles. Overall, the results of this study give policy makers and planners insight into understanding the dynamic nature of individuals’ responses to travel-related strategies, as well as differences between the responses to congestion that are assumed by policy makers and those that are actually adopted by individuals.