Node-based scheduling method for easy migration from CAN to FlexRay in in-vehicle networking systems

As vehicles become more intelligent, in-vehicle networking (IVN) systems such as controller area network (CAN) are essential for the convenience and safety of drivers. To expand the applicability of IVN systems, attention is currently being focused on chassis networking systems that require increased network capacity and real-time capabilities. FlexRay was developed to replace CAN protocol in chassis networking systems, to remedy the shortage of transmission capacity and unsatisfactory real-time transmission delay of conventional CAN. However, FlexRay network systems require a complex scheduling method, which is a barrier to their implementation as chassis networking systems. In particular, if we want to migrate from a CAN network to a FlexRay network using the well-defined CAN message database, which has been specifically constructed for chassis networking systems by automotive vendors, a new type of scheduling method is necessary to reduce scheduling efforts during the software development process. This paper presents a node-based scheduling method for easy migration from a CAN network to a FlexRay network system. To demonstrate the feasibility of the technique, its performance is evaluated in terms of various software complexity indices.     

Nanoparticle emission characteristics and reduction strategies by boost pressure control and injection strategies in a passenger diesel engine

This research attempted to analyze nanoparticles and other harmful exhaust emissions in accordance with injection strategies and air-fuel ratio (AFR) changes for small diesel engines. The emission characteristics were analyzed in the medium-speed condition, which is the main driving range of a diesel engine. In the case of particulate matter (PM), the number of particles was measured, analyzed, and compared to identify the correlation and emission characteristics of nanoparticles by using a dilution device and condensation particle counter (CPC), which are international standards for particle measurement recommended by the Particulate Measurement Programme (PMP). The engine torque tended to be reduced as pilot injections were added, and the torque was increased by the increased boost pressure, but reduced by the exhaust pressure increase in a part of the low-load range. The number of nanoparticles was not influenced greatly by the change in AFR, but the reduction effect on the PM weight was great depending on the boost pressure increase. In addition, the number of nanoparticles tended to increase as the fuel injection timing became closer to TDC in all conditions, and its difference became larger with an increase in AFR. In addition, in the case of the pilot injection, nanoparticle emission showed similar characteristics depending on the main injection timing, but it was increased by advanced injection timing when performing the main injection only, and the number of the nanoparticles increased as pilot injections were added. Last, the optimal conditions for EMS calibration were analyzed by selecting the conditions of torque reduction and NOx increase within 5 % from all of the engine operating conditions; optimized conditions are presented.     

Quantifying travel time variability at a single bottleneck based on stochastic capacity and demand distributions

Travel time reliability, an essential factor in traveler route and departure time decisions, serves as an important quality of service measure for dynamic transportation systems. This article investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. A volume-to-capacity ratio-based travel time function and a point queue model are used to demonstrate how day-to-day travel time variability can be explained from the underlying demand and capacity variations. One important finding is that closed-form solutions can be derived to formulate travel time variations as a function of random demand/capacity distributions, but there are certain cases in which a closed-form expression does not exist and numerical approximation methods are required. This article also uses probabilistic capacity reduction information to estimate time-dependent travel time variability distributions under conditions of non-recurring traffic congestion. The proposed models provide theoretically rigorous and practically useful tools for understanding the causes of travel time unreliability and evaluating the system-wide benefit of reducing demand and capacity variability.     

Hybrid neural network model for history-dependent automotive shock absorbers

The method of numerical multi-body simulation is an often used and well-understood development tool in the automotive industry. In order to reproduce the ride comfort or handling behaviour of vehicles, mathematical models have to be built up. To achieve accurate simulation results, highly detailed component models are required. However, the formulation of appropriate physically-based model equations of complex automotive components (e.g. air springs, shock absorbers, rubber bearings, tyres, etc.) can be very difficult. To handle this, empirical modelling methods have been developed. Simple algebraic equations are used to describe complex system behaviour. This simplification is very effective, although it largely ignores the natural laws of mechanics and thermodynamics but is still capable to predict the component response. This article illustrates how to take advantage of this approach in numerical simulations. We describe the development of a hybrid automotive shock absorber model based on both spline and neural network (NN) approaches. By combining these different approaches, an accurate model is achieved without loss of variability. Non-isothermal laboratory force-displacement measurements of an automotive shock absorber are being used to estimate the parameters of the NN. As shown, the model replicates the measured data with sufficient accuracy, especially the hysteresis. Finally, we present a set of quarter-car simulations with a built-in hybrid NN shock absorber.     

Adaptive neuron control using an integrated error approach with application to active suspensions

This paper proposes a new neuron control strategy for an active vehicle suspension system, with the emphasis on the study of multivariable and uncertain suspension characteristics. The novelty of this strategy is in the use of integrated error, which consists of multiple output errors in the regulated plant. By combining the integrated error approach with the traditional neuron control (TNC), integrated error neuron control (IENC) is presented. It provides a direct control to the multiple outputs of the control plant simultaneously. Taking a quarter-car model as an example, the proposed control strategy is applied and comparative simulations are carried out with various vehicle parameters and road input conditions. Simulation results prove the effectiveness and robustness of the proposed IENC method. In addition, the newly proposed neuron scheme provides a simple yet efficient new possibility for the control of a class of uncertain multivariable systems similar to an active vehicle suspension.     

Analysis of the capabilities of a two-stage turbocharging system to fulfil the US2007 anti-pollution directive for heavy duty diesel engines

This article presents a two-stage turbocharged heavy-duty diesel (HDD) engine designed to fulfil the US2007 anti-pollution directive. This directive imposes very restrictive limits on the NOx and particle emissions of HDD engines. In this work, the possibility of combining particle traps in the exhaust line to reduce soot emissions with very high EGR rates to reduce NOx emissions is considered. This new generation engine implements two-stage turbocharging in order to improve the bsfc when the engine is working on steady conditions as well as to optimize the engine transient response. After carrying out the tests, the results were analyzed and the engine settings were adjusted to maximise its behaviour and minimise pollutant emissions. NOx and soot emission peaks were also analyzed at engine transient conditions in order to keep them under certain levels, and thus maintain the overall pollutant emissions to a level that is as low as possible. In summary, a double-stage turbocharging configuration can greatly improve engine driveability (between 23% and 36% depending on engine speed), while reducing NOx emissions during transient evolution without increasing opacity peaks beyond the stated limits.     

Analysis process of a steering system using a concept model for idle vibration

This paper describes the development of an optimal design process for a steering column system and supporting system. A design guide is proposed at the initial concept stage of the development process to obtain sufficient stiffness of the steering system while reducing the idle vibration sensitivity of the system. Case studies on resonance isolation are summarized, where vibration modes among the systems are separated by applying a vibration mode map at the initial stage of the design process. This study also provides design guidelines for an optimal dynamic damper system using a CAE (computer aided engineering) analysis. The damper FE (finite element) model is added to the vehicle model to analyze the relation between the frequency and the sensitivity of the steering column system. This analysis methodology makes it possible to achieve target performance in the early design stage and reduction of damper tuning activity after the proto car test stage. Through the proposed steering column system development process, a lightweight vehicle with high stiffness is possible prior to the proto build stage. Furthermore, the improved process is expected to contribute to reducing the overall development period and the number of proto car tests necessary to achieve the desired steering system performance.     

Thermal design of automobile exhaust based thermoelectric generators: Objectives and challenges

The potential for thermoelectric power generation (via waste heat recovery onboard automobiles) to displace alternators and/or provide additional charging to a vehicle battery pack has increased with recent advances in thermoelectric material processing. In gasoline fueled vehicles (GFVs), about 40% of fuel energy is wasted in exhaust heat, while a smaller amount of energy (30%) is ejected through the engine coolant. Therefore, exhaust-based thermoelectric generators (ETEG) have been a focus for GFV applications since the late 1980s. The conversion efficiency of modern thermoelectric materials has increased more than three-fold in the last two decades; however, disputes as to the thermal design of ETEG systems has kept their overall efficiency at limited and insufficient values. There are many challenges in the thermal design of ETEG systems, such as increasing the efficiency of the heat exchangers (hot box and cold plate), maintaining a sufficient temperature difference across the thermoelectric modules during different operating conditions, and reducing thermal losses through the system as a whole. This paper focuses on a review of the main aspects of thermal design of ETEG systems through various investigations performed over the past twenty years. This paper is organized as follows: first, the construction of a typical ETEG is described. The heat balance and efficiency of ETEG are then discussed. Then, the third section of this paper emphasizes the main objectives and challenges for designing efficient ETEG systems. Finally, a review of ETEG research activities over the last twenty years is presented to focus on methods used by the research community to address such challenges.     

Comparison of HC species from diesel combustion modes and characterization of a heat-up doc formulation

This study summarizes engine speed and load effects on HC species emissions from premixed charge compression ignition (PCI) and conventional diesel combustion, and it evaluates diesel oxidation catalyst (DOC) formulations on a gas flow reactor for the purpose of diesel particulate filter regeneration or lean NO_x trap desulfation. HC emissions are sampled simultaneously by a Tedlar bag for light HC species and by a Tenax TA™ adsorption trap for semi-volatile HC species, and they are analyzed by gas chromatography with a flame ionization detector. The bulk temperature and residence time during combustion are key parameters that are important for understanding the effects of speed and load on engine-out HC emissions. The degree of post-flame oxidation is higher in PCI than in conventional combustion, and it is increased for PCI with a higher speed and load, as indicated by a lower fuel alkanes/THC ratio, a higher alkenes/fuel alkanes ratio, and a higher methane/THC ratio. Ethene and n-undecane are two representative HC species, and they are used as a surrogate mixture in the gas flow reactor to simulate PCI and conventional combustion with in-cylinder post fuel injection. Among the three DOC formulations tested, the catalyst with constituent precious metals of platinum and palladium (PtPd) showed the best light-off performance, followed by PtPd with an addition of cerium dioxide (PtPd+CeO₂), and platinum (Pt), regardless of exhaust compositions. Conventional combustion exhaust composition shows a lower light-off temperature than that of PCI, regardless of catalyst formulation.     

怎样卖掉你的车

在汽车消费发达的国家，二手车消费是整个汽车消费的重要组成部分。甚至可以说，科学、合理、完善的二手车消费体制带动了整个汽车消费的发展。在今天的中国，汽车越来越多地进入了家庭，准备置换手中旧车的人也越来越多，所以《爱车》特别邀请美国二手车销售专家M.Brueggemann先生为中国的车主朋友奉献一篇精彩的文章，虽然本文充满美国社会的气息，很多技巧不能直接套用，但是先进的经验是绝对值得借鉴的。[编者按]