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The adoption of electric vehicles (EVs) has been announced worldwide with the aim of reducing CO2 emissions. However, a significant increase in electricity demand by EVs might impact the stable operation of the existing power grid. Meanwhile, EV charging is acceptable to most users if it is completed by the time of the next driving event. From the viewpoint of power grid operators, flexibility for shifting the timing of EV charging would be advantageous, including making effective use of renewable energy. In this work, an EV model and simulation tool were developed to make clear how the total charging demand of all EVs in use will be influenced by future EV specifications (e.g., charge power) and installation of charging infrastructure. Among the most influential factors, EV charging behavior according to use cases and regional characteristics were statistically analyzed based on the real-world usage data of over 14, 000 EVs and incorporated in the simulation tool.

This paper proposes a method of estimating road friction and tire slip angle in a cornering maneuver. The method can estimate front tire road friction accurately at low lateral acceleration because it is based on the tire self-aligning torque (SAT) that exhibits high sensitivity to road friction at low slip angles. Road friction and tire slip angle, which are mutually interdependent, are estimated simultaneously using an extended Kalman filter designed around a model describing the relationship between road friction and SAT and a vehicle lateral dynamic model. The front tire SAT is calculated with a mathematical model that describes the torque transmission characteristics from the electric power steering torque to SAT. Therefore, the proposed method is readily applicable to production vehicles. Results of an experimental study show that the change in road friction is instantaneously estimated at low lateral acceleration.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

Prediction of the discharge path behavior between electrodes on a spark plug is important for efficient energy use in internal combustion engines, especially in lean combustion. In this paper, we propose a numerical model for the prediction of the spark path behaviors based on the coupling of a flow field, a Lagrangian particle model, and an equivalent circuit model. A turbulent flow around cylinders imitating electrodes is solved using a direct numerical simulation, in which Lagrangian particles along the spark path are tracked. Electric current and inter-electrode voltage are computed based on the energy conversion rate from the circuit to the mixture gas. As a result, a discharge path is reproduced with Lagrangian tracking particles virtually aligned between the cylinders. The spark path has a complicated structure along the spanwise direction due to the complex three-dimensional vortical structure of the cylinder wake.

In recent years, the number of reported traffic accidents due to sudden deterioration in driver’s physical condition has been increasing, it is expected to develop a system that prevents accidents even if physical condition suddenly changes while driving, or reduces damage through vehicle body control. For this purpose, it is necessary to detect sudden changes of the driver’s physical condition, and research is being conducted widely. Among them, it is reported that some of such changes may appear in the heartbeat interval. In other words, by acquiring the driver’s heartbeat interval in real time, it may be possible to detect the sudden changes, and reduce traffic accident. Even if a traffic accident occurs, the damage can be reduced by emergency evacuation immediately after detecting sudden changes.

Idle speed reduction is one of the important solutions for fuel economy improvement. However, idle speed reduction requires improving the disturbance rejection performance of idle speed control to prevent malfunctions such as engine stall. In mass production engines, PID control is mainly used for the idle speed control because of easiness of the design. However the idle speed control system has nonlinear characteristics. Therefore we have developed the algorithm based on the sliding mode control(SMC) [1]. As a result, superior performance was obtained [2]. Furthermore, for performance, we developed the new algorithm based on Tuning Functions (TF) [3]. As a result, high disturbance rejection performance was obtained.

This paper presents a new method for calculating optical flow using data from a high frame-rate camera. We focused on a feature of image data captured with a high frame-rate camera in which objects do not move more than one pixel between successive frames. This approach eliminates repetitive processing for object identification among frames taken at different sampling times. High-speed processing hardware architecture was designed with sequential processing only, and the algorithm was implemented in a field programmable gate array. The resultant unit can calculate optical flow for a 640×120 pixel size image with a 480-Hz processing cycle and 0.5-μsec processing latency.

This paper describes the method used to design the basic control algorithm of a lane-keeping support system that is intended to assist the driver's steering action. Lane-keeping control has been designed with steering torque as the control input without providing a minor loop for the steering angle. This approach was taken in order to achieve an optimum balance of lane-keeping control, ease of steering intervention by the driver and robustness. The servo control system was designed on the basis of H2 control theory. Robustness against disturbances, vehicle nonlinearity and parameter variation was confirmed by μ - analysis. The results of computer simulations and driving tests have confirmed that the control system designed with this method provides the intended performance.

We are developing some head clearance measurement system based on image processing and stereo method. Two shading images (a right and left) obtained by a stereo camera are transformed to binary images, and some corresponding features are searched between both images. An important matter of this image processing is an availability under every condition of environment and the process must be managed with suitable methods. In this paper, the structure and the algorithms of our system are described and some experimental results also introduced.

This Paper Presents the world's first active noise system for production vehicle implementation. Adopted in the new middle size FF car model, this epoch-making system dramatically reduces the booming noise caused by the second-order harmonic of engine revolution. This is accomplished by using an adaptive control theory based on digital signal processing technology and a digital signal processor (DSP). The system basically employs a multiple error filtered-x LMS algorithm, to which an new algorithm was added to achieve the maximum noise reduction effect under a condition of stable control in a compact system for production vehicle application.

An analysis was made of vibration phenomena in the steering system of a vehicle, when the front wheels have some amount of unbalance. The program included vehicle running tests and bench tests to ascertain some of the factors influencing vibration behavior. A mathematical model of the vibration system was simulated on a digital computer in as much detail as possible. The resultant understanding of the dynamics of the system as a whole led to an extensive theoretical analysis of selected key parameters.

In order to study the potentiality of the modification of the combustion rate for NOx formation control in the spark ignition (SI) engine, the authors first developed a new mathematical model by assuming the stepped gas temperature gradient in the cylinder. The predicted results from this new mathematical model show good coincidence with the experimental data. Second, the authors discuss the effects of the modification of the combustion rate on NOx formation using the new mathematical model. It was concluded that NOx formation in the premixed SI engine would be essentially determined by the specific fuel consumption only, regardless of any modification of the engine combustion rate.

New image processing procedures for speckle photography and holographic interferometry are described. The algorithm for speckle photography measures the displacement value and direction automatically within the accuracy of ±5% over a range of 10 µm to 150 µm. This algorithm has adopted the Maximum Entropy Method to measure fringe intervals with high accuracy. The algorithm for holographic interferometry detects the fringe line and determines the displacement distribution with an operator's assist. Through the experiments, it was shown that these procedures are effective and accurate for vibration and deformation analysis.

Two working groups in the JSAE Committee of Fatigue–Reliability Section1 are currently researching the issue of fatigue life by both experimental and the CAE approach. Information regarding frequent critical problems on arc–welded structures were sought from auto–manufacturers, vehicle component suppliers, and material suppliers. The method for anti–fatigue design on arc–welded structures was established not only by a database created by physical test results in accordance with the collected information but also with design procedure taking Fracture–Mechanics into consideration. This method will be applied to vehicle development as one of the virtual laboratories in the digital prototype phase. In this paper, both the database from bench–test results on arc welded structures and FEA algorithm unique to JSAE are proposed some of the analysis results associated with the latter proposal are also reported.

A new integrated control system has been developed for controlling an SI engine and a CVT proactively so as to obtain the demanded drive torque most efficiently. Taking into account ease of calibration, a control system configuration has been achieved that determines the CVT ratio from the target drive torque and vehicle speed, based on the steady-state relationship between the demanded drive torque and the vehicle speed, gear ratio, engine torque and fuel economy. An analysis was made of drive torque characteristics while the ratio was changing under transient conditions. The results showed that using engine torque to compensate for the ratio change response lag and inertia torque, which is proportional to the differential of the gear ratio, is effective in improving drive torque responsiveness.

A CVT variator chain system is superior in transmission efficiency to a belt system because of its lower internal friction. However, a chain produces more noise than a belt due to the long pitch length of contact between the pulleys and rocker pins. This study focuses on optimization of the pitch sequence for reducing chain noise. The previous pitch sequence was suitably combined of links of different lengths to improve noise dispersibility for reducing chain noise. First, the object function was defined as the reduction of the peak level of 1st-order chain noise combined with a well-balanced the levels on the low and high frequency sides. Interior background noise consisting of road noise and wind noise have the characteristic that they increase as the frequency decreases.