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In electrified automobiles, wind noise significantly contributes to the overall noise inside the cabin. In particular, underbody airflow is a dominant noise source at low frequencies (less than 500 Hz). However, the wind noise transmission mechanism through a battery electric vehicle (BEV) underbody is complex because the BEV has a battery under the floor panel. Although various types of underbody structures exist for BEVs, in this study, the focus was on an underbody structure with two surfaces as inputs of wind noise sources: the outer surface exposed to the external underbody flow, such as undercover and suspension, and the floor panel, located above the undercover and battery. In this study, aero-vibro-acoustic simulations were performed to clarify the transmission mechanism of the BEV underbody wind noise. The external flow and acoustic fields were simulated using computational fluid dynamics.

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 study focused on European NCAP activities of introducing a new head protection evaluation procedure, as proposed by BASt (Federal Highway Research Institute - GERMANY). Various kinds of E-bikes are available in the market, ranging from E-bikes that have a small motor to assist the rider’s pedal-power i.e., pedelecs to somewhat more powerful E-bikes which is similar to a moped-style scooter. This paper focused on identifying the factors influencing bicyclist head kinematics during bicycle vs. passenger vehicle (PV) collisions at the intersection. Two AM50 bicyclist FE models are developed using i) GHBMC Human Body Model (HBM) and ii) WorldSID (WS) side impact dummy. Head kinematics of bicyclists of pedal-assist E-bike and normal bike were compared using CAE simulation. It is found that the vehicle’s impact velocity, type of bicycle, the mass of E-bike and bicycle traveling speed will influence the head kinematics.

Riding comfort on the seat is one of the important factors for vehicle comfort. To analyze riding comfort, there were some models for predicting human vibrations in the past studies. On the other hand, it is strongly affected by human body motion caused by vehicle excitation during driving especially low frequency, but it is difficult to predict human motion due to an unclear mechanism of muscle reflex. The purpose of this study is to construct virtual riding comfort testing simulation based on virtual prototyping of the seat. In this study, a virtual occupant model that predicts occupant motion on the seat against external excitation including muscle reflex for maintaining sitting posture constructed. The whole body was modeled as 15 segments biomechanical model (1D) with wobbling mass. Each joint has passive elastic torque and damping torque springs. Human body surface was modeled as rigid shape.

Because of rising demands to improve aerodynamic performance owing to its impact on vehicle dynamics, efforts were previously made to reduce aerodynamic lift and yawing moment based on steady-state measurements of aerodynamic forces. In recent years, increased research on dynamic aerodynamics has partially explained the impact of aerodynamic forces on vehicle dynamics. However, it is difficult to measure aerodynamic forces while a vehicle is in motion, and also analyzing the effect on vehicle dynamics requires measurement of vehicle behavior, amount of steering and other quantities noiselessly, as well as an explanation of the mutual influence with aerodynamic forces. Consequently, the related phenomena occurring in the real world are still not fully understood.

Variable flux permanent magnet synchronous machines (VFPMSMs) have been designed by using finite element analysis (FEA) to evaluate speed-torque capability considering requirement for magnetization state (MS) manipulation. However, due to its unique characteristic to change the MS, numerous combinations of design parameters need to be evaluated to achieve a final design. To accelerate the design process, this paper presents a method that consists of an equivalent magnetic circuit model and a process to obtain magnet width and thickness that satisfy target maximum torque and power factor (P.F.) capability. This model includes magnet operating point analysis under given magnet width and thickness condition to achieve target MS and avoid demagnetization at full load. This analysis provides desired stator magnetomotive force, magnet and stator induced flux linkage. Therefore, expected torque and P.F. capability is calculated.

Road Noise is generated by the change of random displacement input inside the tire contact patch. Since the existing 3 or 6 directional electromagnetic shakers have a flat surface at the tire contact patch, these shakers cannot excite the vehicle in a manner representative of actual on-road road noise input. Therefore, this paper proposes a new experimental method to measure the road noise vehicle transfer function. This method is based on the reciprocity between the tire contact patch and the driver's ear location. The reaction force sensor of the tire contact patch is newly developed for the reciprocal loud speaker excitation at the passenger ear location. In addition, with this equipment, it is possible to extract the dominant structural mode shapes creating high sound pressure in the automotive interior acoustic field. This method is referred to as experimental structure mode participation to the noise of the acoustic field in the vibro-acoustic coupling analysis.

A flag is a global boolean variable used to achieve synchronization between various tasks of an embedded system. An application implementing flags performs actions or events based on the value of the flags. If flag variables are not implemented properly, certain synchronization related issues can arise which can lead to unexpected behavior or failure of the underlying system. In this paper, we present an automated verification technique to identify and verify flag usage patterns at an early stage of code development. We propose a two-step approach which consists of: a. identification of all potential flag variables and b. verification of flag usage patterns against predefined set of rules. The results of our experiment demonstrate that the proposed approach reduces the cost and complexity of the flag review process by almost 70%.

This paper describes a control method to improve straight-line stability without sacrificing natural steering feel, utilizing a newly developed steering system controlling the steering force and the wheel angle independently. It cancels drifting by a road cant and suppresses the yaw angle induced by road surface irregularities or a side wind. Therefore drivers can keep the car straight with such a little steering input adjustment, thus reducing the driver's workload greatly. In this control method, a camera mounted behind the windshield recognizes the forward lane and calculate the discrepancy between the vehicle direction and the driving lane. This method has been applied to the test car, and the reduction of the driver's workload was confirmed. This paper presents an outline of the method and describes its advantages.

This paper describes the development of the drive motor adopted on the newly developed 2013 Model Year (MY) electric vehicle (EV). Based on the 2011MY EV that was specifically designed and engineered for mass-production, the 2013MY powertrain integrates the electric motor, inverter and charging system into one unit in order to achieve downsizing and weight saving, unlike previous 2011 model which had these components segregated. In general, integration of all components into one unit causes deterioration of the noise and vibration performance of vehicles due to an increase in weight and the number of resonance parts. In order to overcome such problems associated with this integration, each component in the 2013 model has been optimized to reduce noise and vibration resulting in high degree of vehicle quietness.

This paper describes a variable magnetomotive force interior permanent magnet (IPM) machine for use as a traction motor on automobiles in order to reduce total energy consumption during duty cycles and cut costs by using Dy-free magnets. First, the principle of a variable magnetomotive force flux-intensifying IPM (VFI-IPM) machine is explained. A theoretical operating point analysis of the magnets using a simplified model with nonlinear B-H characteristics is presented and the results are confirmed by nonlinear finite element analysis. Four types of magnet layouts were investigated for the magnetic circuit design. It was found that a radial magnetization direction with a single magnet is suitable for the VFI-IPM machine. Magnetization controllability was investigated with respect to the magnet thickness, width and coercive force for the prototype design. The estimated variable motor speed and torque characteristics are presented.

In order to enhance product attraction, it is important to reduce the impact noise when a vehicle go over bumps such as bridge joints. Vehicle performance to transitional noise phenomena is not yet analyzed well. In this paper, a prediction method is established by vector composition and inverse Fourier transform with the combination of Multibody Dynamics (MBD) and FEM. Also, a root cause analysis method is established with the following three mechanism analysis methods; transfer path analysis, mode contribution analysis, and panel contribution analysis.

Electric Vehicles are very quiet at low speeds therefore people (especially the visually impaired) have difficulty recognizing that these vehicles are approaching. To address this concern, Approaching Vehicle Sound for Pedestrians system development has been discussed worldwide. In Japan, USA, Europe and China, government regulation is currently under study. As a solution to meet this concern, Nissan has developed the VSP (Approaching Vehicle Sound for Pedestrians) system for implementation on Nissan's first mass production Electric Vehicle. Nissan VSP emits a futuristic sound to satisfy 3 key stakeholders' concerns; for pedestrians to provide detectability, for drivers and neighborhoods to maintain a quiet environment. The sound emitted during forward motion has a “twin peaks and one dip” frequency signature, with modulation (or rhythmic structure) to accommodate human-beings ear frequency sensitivity, hearing loss due to aging and ambient noise conditions.

At Nissan we have developed a new parallel hybrid system for rear-wheel-drive hybrid vehicles. As the main components of the hybrid system, both the motor and the inverter have been developed and are manufactured in house to attain high power density for providing responsive acceleration, a quiet EV drive mode and improved fuel economy. Because the motor is located between the engine and the transmission, it had to be shortened to be within the length allowed for the powertrain. Therefore, new technologies have been developed such as high-density, square-shaped windings and an optimized magnetic circuit specially designed for concentrated winding motors. The inverter is sized to a 12V battery, which it replaces in the engine compartment. Despite its compact size, the inverter must have rather large current capacity to drive a high-power motor. Heat management is critical to the design of a small but high-power inverter.

This paper deals with a blind spot assistance system that assists the driver by generating yaw-moment when a driver's lane change maneuver is detected and when there is an object present in the blind spot area of the adjacent lane. The system combines lane information and driver's maneuver information for estimating the driver's lane change. If the millimeter wave sensor detects an object in the rear blind spot area in the event of a lane change, direct yaw-moment in the opposite direction of the lane change maneuver is generated. The unique method of detecting driver's lane change, control method of assisting the driver to recover back in lane, and the system design to maintain driver compatibility is mentioned, together with the effectiveness of the system.

This paper describes the motor and inverter system developed for the Nissan LEAF that has been specifically designed as a mass-produced electric vehicle. The system produces maximum torque of 280 Nm and maximum power of 80 kW. The motor achieves a small size, high power, and high efficiency as a result of adopting the following in-house technologies. The magnetic circuit design was optimized for an interior magnet synchronous motor to attain the maximum performance figures noted here. The material technologies of the rotor and the stator facilitate high efficiency and the production technology achieves high density winding. The cooling mechanism is optimally designed for a mass-produced electric vehicle. The inverter incorporates the following original technologies and application-specific parts to obtain cost reductions combined with reliability improvements. The power module has an original structure with the power devices mounted directly on the busbars.

In making driver workload assessments, it is important to evaluate the driver's level of brain activity because the operation of a motor vehicle presumably involves higher-order brain functions. Driving on narrow roads in particular probably imposes a load on the driver's brain functions because of the need to be cognizant of the tight space and to pay close attention to the surroundings. Test vehicles were fitted with a functional near-infrared spectroscopy (fNIRS) system for measuring bloodstream concentrations at 32 locations in the frontal lobe of the participating drivers in order to evaluate their levels of mental activity while driving on narrow roads. The results revealed significant increases in cerebral blood flow corresponding to the perceived workload. This suggests that increases in cerebral blood flow can be used as an effective index for estimating mental workloads.

This paper describes the HMI, navigation and telematics systems developed specifically for the Nissan LEAF electric vehicle to dispel drivers' anxieties about operating an EV. Drivers of EVs will need to understand various new kinds of information about the vehicle's operational status that differ from conventional gasoline-engine vehicles. Additionally, owing to the current driving range of EVs and limited availability of charging stations, drivers will want to know acccurate the remaining driving range, amount of power and the latest information about charging station locations. It will also be important to ensure that people unfamiliar with EVs will be able to operate them easily as rental cars or in car-sharing systems without experiencing any inconvenience.

The probability or risk of traffic accidents must be estimated quantitatively in order to implement effective traffic safety measures. In this study, various statistical data and probability theory were used to examine a method for predicting the risk of crossing-collisions, representing a typical type of accident at intersections in Japan. Crossing-collisions are caused by a variety of factors, including the road geometry and traffic environment at intersections and the awareness and intentions of the drivers of the striking and struck vehicles. Bayes' theorem was applied to find the accident probability of each factor separately. Specifically, the probability of various factors being present at the time of a crossing-collision was estimated on the basis of traffic accident data and observation survey data.

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.