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A number of automobiles have been fitted with electric motors and their inverters. In order to reduce the space of the motors, we have proposed a 2-controllable-rotor motor which consists of 2 rotors and 1 stator. However, this motor is driven by a 6-phase inverter, and the inverter size is almost the same as that for 2 motors driven by 3-phase inverters. In this paper, we propose a 2-controllable-rotor motor driven by a 5-phase current, and its operation principle is described. Furthermore, its characteristics are investigated using finite element analysis.

This paper proposes a dynamic simulation method of a magnetic gear using its torque map. The phase angle difference between the input and output rotors depends on a load of the output rotor. The load contains an external load and brake torque due to internal mechanical and iron losses. In this situation, the dynamic performance of a magnetic gear is computed by a transient analysis using a motion equation, and the computation cost is large. In order to reduce the computation cost, a dynamic simulation method using a torque map is proposed and discussed.

A magnetic geared motor has been developed as a low speed and high torque motor. However, it is difficult to increase the gear ratio due to the constraint of the number of poles. In order to solve this problem, a radially-differential type magnetic harmonic geared motor is proposed. It can easily increase the gear ratio up to approximately several hundred. In this paper, the structure and operational principle are described. Finally, the torque characteristics are investigated using 3-D finite element method (FEM).

Traction motors of electric vehicles require wide power band characteristics. A magnetic-geared motor has a possibility to achieve these requirements because it has passively variable magnetic flux characteristics. In this paper, the passively variable magnetic flux characteristics of the magnetic-geared motor is investigated using finite element analyses. Furthermore, a maximum torque control method for the magnetic-geared motor is proposed and investigated.

Most of electric machines have been fitted with a number of electric motors and their inverters. In order to reduce the space of the motors and inverters, we proposed a motor with two independently controllable rotors using a 6-phase inverter. However, winding factors of 3- and 6-phase rotors were 0.87 and 0.50, respectively, in a conventional winding arrangement. In order to increase the winding factor of the motor, this paper proposes a novel winding arrangement, and its effectiveness is verified using finite element analysis.

This paper investigate the electromagnetic vibration of a 24/20 switched reluctance motor. There are 2 driving methods for the 24/20 switched reluctance motor: pulse drive and vector control. The electromagnetic force and vibration due to these driving methods are compared and investigated. Especially, the electromagnetic force component of 1 stator tooth is compared with that due to the Maxwell’s stress tensor in the air gap using finite element analysis.

Electric vehicles are equipped with a number of electric motors and their inverters. In order to reduce the space of the motors, we have proposed a motor with two concentrically-arranged rotors which can be independently controlled, and a common outer stator. However, the previous motor was difficult to be practically used due to its complicated support structure. Therefore, we proposed an improved motor with two axially-arranged rotors. In this paper, the static and dynamic characteristics of the motor are computed and verified by carrying out measurements on a prototype. Both results were in good agreement, and the effectiveness of the proposed motor was shown.

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications have the potential to not only accelerate progress towards autonomous vehicles but also to facilitate the achievement of more appropriate driver behavior patterns and thus make traffic more energy efficient and environmentally friendly. This paper presents a driving advisory system for vehicles approaching traffic lights that is based on the use of a Green Light Optimal Speed Advisory (GLOSA) system and evaluates its impact on traffic flow characteristics. This system, which assumes the existence of a connection with the traffic light ahead, calculates the distance required to pass through the intersection without stopping during the remaining green signal time. The required distance is then projected onto the road surface as a green planar rectangle shape through a head-up display (HUD). As long as the vehicle is traveling on the green rectangle, the drivers will not need to make a complete stop or accelerate again in order to meet the onset of a green signal. Assuming that all vehicles are equipped with our proposed system, traffic simulations were carried out to evaluate the performance of the scheme. Numerical analyses showed that a higher fuel efficiency and lower carbon dioxide (CO 2 ) emissions were achievable, even under high-density traffic conditions, by combining the full and partial assistance levels of our proposed system.

Rear-end collisions in longitudinal car-following situations occasionally cause severe multiple collision accidents, especially in high-density and high-speed traffic situations. However, if a preceding car driver's deceleration intention could be inferred in advance, even a second earlier, the risk of a collision could be decreased not only between vehicle pairs but also for car platoons. This paper reports on the application of our previously reported intent inference system to a platoon of vehicles and evaluates its impact on safety. The system utilizes an unscented Kalman filter (UKF) and attempts to infer the intent of a vehicle ahead 1.5 s in advance of its driver's most likely action. The inferred intention is then provided to the driver of the assisted vehicle through an interface based on a windshield display, and earlier experiments have proved that the system is quite effective for collision risk mitigation. In this paper, we report on an investigation into the safety impacts of our system on a platoon of vehicles following an assisted vehicle. The results of a traffic simulator experiment showed that the system could provide significant safety benefits to multiple cars traveling behind an assisted vehicle in a vehicle platoon.

A current superimposition variable flux reluctance motor for a traction motor of electric vehicles and hybrid electric vehicles are proposed. This motor can be driven using a 6-phase asymmetric inverter which is used to drive a switched reluctance motor. However, it is difficult to obtain a high efficiency in a low-speed and high-torque region. In order to solve this problem, a switching operation between the current superimposition variable flux reluctance motor and a switched reluctance motor is proposed in this paper.

The electrification of automobiles has been gaining momentum recently, and more and more automobiles are being fitted with electric motors and their inverters. In order to reduce the space of the motors and inverters, a motor with two controllable rotors was proposed [1- 2]. This motor has two rotors and one stator. The two rotors can be independently controlled using 3- and 6-phase superimposed currents created by a 6-phase inverter. One rotor is driven by a 3-phase current and the other is driven by a 6-phase current. However, this motor has problems such as low heat dissipation and complicated support structure of the stator because the stator is sandwiched between the two rotors. In order to solve these problems, a motor with its stator on the outside of its rotors was proposed [3]. This motor has also two rotors and one stator, and the two rotors can be independently controlled using 3- and 6-phase superimposed currents. However, this motor has also a problem of a complicated support structure of the middle rotor. Therefore, we proposed a novel motor with two controllable rotors to solve above problems [4]. In this paper, 3D-FEM analysis coupled with vector control is conducted in order to verify that the two rotors can be independently controlled.

Rear-end collisions occasionally cause severe multiple-collision accidents, especially in high-density and high-speed traffic. Avoiding the rear-end collisions is one of the critical issues since this type of collision has been the most significant factor among all types of traffic accident for many years. This research aims to develop a driver assistance system that informs the inferred intention of preceding car's deceleration behavior to the following vehicle through an interface based on a wind shield display (W SD). Assuming four vehicles forming a longitudinal platoon, a system was developed in which the deceleration intent of the 3rd vehicle is inferred and informed to the 4th vehicle driver by the WSD. A driving simulator (DS) experiment was carried out to evaluate the performance including the collision risk of the 4th vehicle with and without the system. A series of the experiments showed that the proposed system was significantly effective to mitigate the collision risk even under emergency deceleration scenarios.

This study examines the use of a humanoid robot for not only entertainment but also industrial tasks in a human-occupied environment. An impact task model based on input shaping control of a robot hand equipped with a flexible rubber stick (RS) is discussed and its efficacy is demonstrated. To maintain safety, limited space and a low-power servo motor are considered. The input shaping amplifies necessary vibration while reducing unnecessary vibration. The humanoid robot performs the impact task with high accuracy using the flexible RS and also realizes efficient motion via a double arm. The proposed approach has potential for both industrial and entertainment applications of a humanoid robot in a human-occupied environment.

This paper focused on the remaining time to brake pedal operation (TTBP) and proposed the unscented Kalman filter (UKF)- and particle filter (PF)-based models to estimate the TTBP prior to the actual brake pedal operation. The state and measurement equations were simply modeled by partially using an ANN model. Also, the three-vehicle convoy data collected through a driving simulator (DS) experiment showed that the first car started decelerating and shortened the headway two to three seconds before the brake pedal operation. This made sure that the proposed UKF and PF could be applied to the estimation of TTBP by simply measuring the velocity and headway of the preceding cars.

This paper applies a particle filter (PF) and a dual particle filter (DPF) for estimating the headway distance of vehicles traveling in a longitudinal platoon. Assuming that prior knowledge on the model parameter is different from what is observed in a real car-following, PF attempts to estimate the headway by measuring the acceleration rate and velocity of probe cars installed in the platoon. In addition, DPF is proposed to improve the accuracy by estimating the headway as well as the model parameters simultaneously within a single process. Numerical analyses were carried out to evaluate the performance of PF and DPF in two scenarios with six-vehicle platoon and different installation of probe cars. It was found that PF and DPF perform very well if all traveling vehicles in the platoon measure the acceleration rate and velocity. However, the effect of dual filtering process in DPF is not very significant to improve the estimation accuracy because the model parameters are not corrected appropriately by the dual filtering process.

In this study, an applicability of microscopic shockwave (μSW) theory is evaluated whether it is efficient in assessing the risk of rear-end collision in vehicle platoon. Two different types of μSW behavior are proposed for the evaluation; one is the car-following that shows a higher risk, whereas the other is a low-risk vehicle platooning. The numerical analysis attempts to evaluate whether the conventional risk evaluation approaches are able to distinguish those two cases; high and low risk platooning based on the proposed μSW technique. The statistical analysis showed that the behavior of μSW is capable of assessing the risk of rear-end collision of platooning vehicles.

A dynamic feedback system is developed for estimating the velocity and headway distance in a longitudinal three-vehicle platoon. The estimation system is modeled using an extended Kalman filter (EKF) and a Neural Kalman filter (NKF) that estimate the velocity and headway distance by measuring the acceleration rate of some selected vehicles in the platoon. State equations of the EKF are analytically defined by a discrete conservation equation of vehicle speed and headway distance, whereas the measurement equation is based on a conventional car-following model. The NKF, however, defines both equations using artificial neural network models (ANNs) that enable both equations to be defined without using any analytical equations. Numerical analysis showed that the NKF reduces the estimation errors in most cases even under unexpected car-following situations as the ANNs have the capability of describing nonlinear car-following phenomena. However, some difficulties still remain unsolved in optimizing NKF parameters. It was found that alternate approaches may be required to yield more accurate estimates instead of using NKF.

The Signal Recognition Enhancement System or SRES is one of practical ITS which is expected to avoid rear-end collisions at a signalized intersection by providing signal information to a vehicle and/or a driver before reaching an intersection. This system is also expected to suppress the unnecessary fuel consumption and reduce CO 2 emissions. This paper aims to evaluate the impact of the SRES which will be installed at signalized intersections. We develop the micro traffic simulation model which includes the behavior of a driver with/without SRES to estimate the impact SRES on the traffic flow around an intersection. We employed the time integral of difference of space distance and stopping distance or TIDSS as the indicator for measurement of safety, while we employed the equations to calculate fuel consumption and CO 2 based on an average velocity. Numerical simulation showed that SRES might help to reduce collision, fuel consumption and CO 2 emissions at signalized intersections.