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After the turn of the century, growing social attention has been paid to environmental concerns, especially the reduction of greenhouse gas emissions and it comes down to a personal daily life concern which will affect the purchasing decision of vehicles in the future. Among all the sources of greenhouse gas emissions, the transportation industry is the primary target of reduction and almost every automotive company pours unprecedented amounts of money to reengineer the vehicle technologies for better fuel efficiency and reduced CO2 emission. Besides those efforts paid for sheer improvements of genuine vehicle technologies, NISSAN testified that “connectivity” with outside servers contributed a lot to reduce fuel consumption, thus the less emission of GHG, with two major factors; 1. detouring the traffic congestions with the support of probe-based real-time traffic information and 2. providing Eco-driving advices for the better driving behavior to prompt the better usage of energy.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio for improving thermal efficiency and downsizing the engine based on fuel-efficient operating conditions are good examples of technologies for enhancing gasoline engine fuel economy. A direct-injection system is adopted for most of these engines. Direct injection can prevent knocking by lowering the in-cylinder temperature through fuel evaporation in the cylinder. Therefore, direct injection is highly compatible with downsized engines that frequently operate under severe supercharging conditions for improving fuel economy as well as with high compression ratio engines for which susceptibility to knocking is a disadvantage.

This study investigates the use of machine learning methods for the selection of energy storage devices in military electrified vehicles. Powertrain electrification relies on proper selection of energy storage devices, in terms of chemistry, size, energy density, and power density, etc. Military vehicles largely vary in terms of weight, acceleration requirements, operating road environment, mission, etc. This study aims to assist the energy storage device selection for military vehicles using the data-drive approach. We use Machine Learning models to extract relationships between vehicle characteristics and requirements and the corresponding energy storage devices. After the training, the machine learning models can predict the ideal energy storage devices given the target vehicles design parameters as inputs. The predicted ideal energy storage devices can be treated as the initial design and modifications to that are made based on the validation results.

This paper describes the methods adopted to improve the image quality of the all-around view system. This system uses multiple vehicle-mounted cameras to capture images of the circumstances around the vehicle. The images undergo viewpoint transformation and are synthesized to create a single image seen from a virtual perspective overhead. The specific methods discussed here concern optimization of the design parameters for the camera orientation and a camera calibration method that does not involve physical movement of the cameras.

Laser excitation wavelengths for two-line planar laser-induced fluorescence (PLIF) of 3-pentanone have been optimized for simultaneous imaging of temperature and composition under engine-relevant conditions. Validation of the diagnostic was performed in a motored optical IC engine seeded homogeneously with 3-pentanone. PLIF measurements of the uniform mixture during the compression stroke were used to measure the average temperature and to access the random uncertainty in the measurements. To determine the accuracy of the temperature measurements, experimental average temperatures were compared to values computed assuming isentropic compression and to the output of a tuned 1-D engine simulation. The comparison indicated that the absolute accuracy of the temperature measurements is better than ±5%. Probability density functions (PDFs) calculated from the single-shot images were used to estimate the precision of the measurements.

Negative valve overlap (NVO) is a valve strategy employed to retain and recompress residual burned gases to assist HCCI combustion, particularly in the difficult regime of low-load operation. NVO allows the retention of large quantities of hot residual burned gases as well as the possibility of fuel addition for combustion control purposes. Reaction of fuel injected during NVO increases charge temperature, but in addition could produce reformed fuel species that may affect main combustion phasing. The strategy holds potential for controlling and extending low-load HCCI combustion. The goal of this work is to demonstrate the feasibility of applying two-wavelength PLIF of 3-pentanone to obtain simultaneous, in-cylinder temperature and composition images during different parts of the HCCI/NVO cycle. Measurements are recorded during the intake and main compression strokes, as well as during the more challenging periods of NVO recompression and re-expansion.

The aim of this study is to gain a better understanding of the mechanism of knocking with respect to flame propagation behavior based on 3D simulations conducted with the Universal Coherent Flamelet Model. Flame propagation behavior under the influence of in-cylinder flow was analyzed on the basis of the calculated results and experimental visualizations. Tumble and swirl flows were produced in the cylinder by inserting various baffle plates in the middle of the intake port. A comparison of the measured and calculated flame propagation behavior showed good agreement for various in-cylinder flow conditions. The results indicate that in-cylinder flow conditions vary the flame propagation shape from the initial combustion period and strongly influence the occurrence of knocking.

In December 2006, Nissan announced its Nissan Green Program 2010 (NGP 2010), a mid-term environmental action plan that includes initiatives to reduce vehicle emissions. In line with this plan, the company intends to introduce a new and original hybrid system in fiscal year 2010. Specifically, this system-called the “Infiniti Direct Response Hybrid”-is a one-motor, two-clutch parallel hybrid system that eliminates the need for a torque converter. It will be featured in the 2012 Infiniti M35 Hybrid and provides the following advantages. 1 Significant improvement in fuel economy even in Highway driving 2 Better response and a more direct feeling 3 Lightweight and low cost This one-motor, two-clutch system without torque converter possesses a simple but highly capable architecture that is new to the passenger vehicle segment.

A particle tracking velocimetry (PTV) system has been developed to measure two dimensional velocity fields in a motored axisymmetric engine with a transparent cylinder. The intake flow was seeded with phenolic microballoons (40 μm hollow spheres) and illuminated by a 1 mm thick horizontal sheet of pulsed laser light from a 25 Watt copper vapor laser capable of 30 ns pulses. Photographs containing tracks of dots representing the multiply exposed path of each particle were produced. These images were digitized by a custom scanner capable of 3456 by 5184 pixel resolution and binarized using an iterative threshold routine in order to locate the particles. Software then determined how the individual particles are organized into tracks and presented the results for operator verification. Velocity magnitude and direction were computed for each track and the results were interpolated to a fixed grid for further analysis.

Traction control systems (TCSs) serve to control brake pressure and engine torque, thereby reducing driving wheel spin for improved stability and handling. Systems are divided into two basic types by the brake control configuration. One type is a one-channel left-right common control system and the other is a two-channel individual control system. This paper presents an analysis of these two types of TCS configurations in terms of handling, acceleration, stability, yaw convergence and other performance parameters. The systems are compared with and without a limited-slip differential (LSD) under various road conditions, based on experimental data and computer simulations. As a result of this work, certain Nissan models are now equipped with a new Nissan Traction Control System with a rear viscous LSD (Nissan V-TCS), which provides both the advantages of a rear viscous LSD in a small slip region and a two-channel TCS in a large slip region.

The use of CAE software in developing plastic components has advanced rapidly in recent years. This progress has been supported by the development of practical analytical tools, based on the finite element and boundary element methods, and on the dramatic improvements seen in computer performance. Following the introduction of a flow analysis program in 1982, Nissan has developed and implemented advanced programs for use in developing plastic components and has integrated the programs into a unified in-house system. This system is being utilized at the design and manufacturing stages of interior and exterior trim parts and has produced concrete results in different phases of component development. Work is now proceeding on the development of a system that can simultaneously analyze both the component performance and the factors that need to be considered in the manufacturing process.

Newly designed laboratory measurement system, which reproduces particle number size distributions of both nuclei and accumulation mode particles in exhaust emissions, was developed. It enables continuous measurement of nano particle emissions in the size range between 5 and 1000 nm. Evaluations of particle number size distributions were conducted for diesel vehicles with a variety of emission aftertreatment devices and for gasoline vehicles with different combustion systems. For diesel vehicles, Diesel Oxidation Catalyst (DOC), urea-Selective Catalytic Reduction (urea-SCR) system and catalyzed Diesel Particulate Filter (DPF) were evaluated. For gasoline vehicles, Lean-burn Direct Injection Spark Ignition (DISI), Stoichiometric DISI and Multi Point Injection (MPI) were evaluated. Japanese latest transient test cycles were used for the evaluation: JE05 mode driving cycle for heavy duty vehicles and JC08 mode driving cycle for light duty vehicles.

This paper describes a headway distance control system for platoon driving on an automated highway system (AHS). The system implemented on a test vehicle is described first, followed by a description of a vehicle control method based on the use of throttle and brake actuators. This method makes it possible to obtain the target acceleration and deceleration regardless of the vehicle speed range and the rate of acceleration or deceleration. Experimental and simulation results obtained with this method are presented. A control method is then described that uses inter-vehicle communication and laser radar to maintain a constant headway between vehicles. The results of simulations and driving tests conducted with three vehicles are presented to illustrate that the use of inter-vehicle communication is highly effective in improving headway control performance.

This paper describes the Multi-AV System featured in the 1989 model Nissan Cedric, Gloria, and CIMA. It is composed of a navigation system and an audio-visual system. The former system tracks the location of the vehicle and shows it on a CRT map display. This standalone navigation system has been achieved using a map-matching technique along with a terrestrial magnetic field sensor and wheel speed sensors installed at the wheels. Information on hotels, golf courses, Nissan dealers and other items can be obtained. A CD-ROM is employed as the memory. The audio-visual system consists of a radio, cassette deck, CD player, and TV. The Multi-AV System combines the practicality of a navigation function with the entertainment capabilities of an audio-visual system to satisfy diverse needs.

ASICs (Application-specific ICs) offer one solution to the problems of quality, cost and installability associated with the increasingly larger-capacity Electronic Control Units (ECUs) in automobiles. A method was, therefore, created for designing automotive ASICs. Using the method, three ASICs were developed which, together, incorporate all of the functions of the electronic instrument cluster. The core ASIC contains the speedometer and system functions, and the other two ASICs contain the tachometer and gauge functions, respectively. This set of three ASICs allows an electronic instrument cluster design which is two times more reliable, and one-second the cost that conventional systems (with a micro-processor and discrete components).

This paper presents an improved exhaust emission simulation model that takes into account fuel transportation behavior in order to obtain more precise air-fuel ratio control, which is needed to meet stringent exhaust emission standards. This simulation model is based on experimental formulas for air and fuel behavior in the intake manifold, especially during transient engine operation. Fuel behavior, including the effect of wall flow on the air-fuel ratio, is obtained analytically. Predictions are then made of the exhaust emissions from a car operated under official driving schedules. The new simulation model is a useful tool in the design and development of fuel supply control systems. An outline of the new model is presented first along with a comparison of the calculated and experimental results. The air-fuel ratio control strategy derived with this model is then described.

Nissan Motor has put on the European SUV market a 2.2-L direct-injection diesel engine with a diesel particulate filter (DPF) system that complies with the EURO IV emission regulations. This paper describes the DPF system, cooperative control of a variable geometry turbo (VGT) and exhaust gas recirculation (EGR), and a high-accuracy lambda control adopted for this engine. In order to achieve a compact DPF, the high-accuracy lambda control was developed to reduce variation in engine-out particulate matter (PM) emissions. Moreover, the accuracy of the technique for predicting the quantity of PM accumulation was improved for reliable detection of the DPF regeneration. Prediction error for PM accumulation increases during transient operation. Control logic was adopted to correct the PM prediction according to lambda fluctuation detected by an observer for lambda at cylinder under transient operating conditions. The observer is corrected lambda sensor output.

This paper describes an image processing method for recognizing white lines on the road ahead to accomplish automatic lane tracking. The behavior of detected points on the white lines can be regarded as multi-channel time-series data. The stochastic behavior of each point correlates with not only its own past behavior but also the behavior of other points around it. Behavior is identified by using a multi-variable auto-regressive (AR) model. This method can estimate the road configuration ahead logically even if the points cannot be detected clearly because a line is discontinuous or is hidden by a forward vehicle.

In the past few years, car navigation and cellular phone system are rapidly increased in Japan and vehicle information and communication system (VICS), the public traffic information service started in 1996, accelerates realization of ITS world. This rapid movement causes drivers to want more information on not only traffic jam but also other versatile items like parking availability, weather report and the latest news, etc. via cellular phone network. This paper describes the on-demand information service with the interactive human interface by operators and the development of the information center and the in-vehicle system to realize it.

From the beginning of the 1990s, we have been vigorously investigating a high-performance power source system for application to environmental vehicles, focusing our research and development efforts specifically on lithium-ion batteries. In order to adapt a battery system to the requirements of the target vehicle, battery performance must be predicted and designed more accurately. In the case of hybrid electric vehicles, for example, battery power must be reliably assured. Improving battery power requires quantitative analytical methods as fundamental techniques for understanding the basic processes that take place in a battery. From this perspective, we began constructing a battery simulation model from scratch in the middle of the 1990s concurrently with our battery R&D activities. The model simulates electrode reactions and charge transport and has been used in investigating the influence of these factors on battery performance.