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In this paper, we suggest a novel algorithm to distinguish semi-steady states from various steering patterns and to estimate the stability factor. The algorithm also estimates each stability factor in left and right turns because there could be a case where they differ based on uneven tire wear and so on. The stability factor, which is the turning characteristic of a vehicle, has been treated as constant for most vehicle control systems. However, in fact, it may change in some situations, for example when a vehicle is overloaded. So there is a chance that a driver may be aware of an unusual sensation when vehicle control is designed based on a constant stability factor. We have succeeded in developing an algorithm to estimate the stability factor accurately enough to be able to compensate for it and have confirmed the effectiveness of the algorithm by simulation and vehicle testing as well.

This paper proposes a new Electric Power Steering (EPS) control strategy that improves steering maneuverability especially on slippery roads. In a conventional steering system (including mechanical and hydraulic ones), poor steering wheel returnability associated with reduced alignment torque from the road may lead to awkward handling on slippery roads. In experiments with a test driver, we found that this phenomenon occurs because of the delay in the driver turning the steering wheel to avoid spinning the vehicle. This delay comes from a lower steering wheel returnability than driver expected. Increasing the steering wheel returnability will be effective in avoiding this problem. This can be realized by using the steering angle feedback or the estimated alignment torque feedback. However, the simple feedback of such values will provide drivers with poor road information when the road is slippery.

Recently, development of vehicle control system targeting Full Driving Automation (autonomous driving level 5) has advanced. Some applications of autonomous driving systems like the Lane Keeping Assist system (LKA) and Auto Lane Change system (ALC) (autonomous driving level 1-3) have been put on the market. However, the conventional system using information from front camera, it is difficult to operate in some situations. For example the road that no line, large curvature and number of lane increases or decreases. We propose an autonomous driving system using high accuracy vehicle position estimation technology and a high definition map. An LKA system calculates the target steering wheel angle based on both vehicle position information from the Global Navigation Satellite System (GNSS) and the target lane of high the definition map, according to the method of front gaze driver model. Then, the system controls steering the wheel angle by Electric Power Steering (EPS).

We have developed a driving simulator for Electric Power Steering (EPS), which can be used to evaluate steering maneuverability on low μ roads. The simulator calculates an 11 DOF (degrees of freedom) vehicle motion based on the steering wheel angle, the accelerator pedal position and the brake pedal position which are operated by the driver. A reaction torque corresponding to the alignment torque is applied to the steering shaft using motors. A 3D CG reproducing the view from the cockpit is displayed on a forward screen. The simulator also includes column type EPS, which generates the assist torque. Consequently, the driver feels the steering torque with good reality. The tire model we used is non-linear and it enables us to simulate the vehicle dynamics also on slippery roads. We compared driver behavior in vehicle and simulator tests and found the simulator could evaluate the relationship between steering maneuverability and EPS control strategy even when the road was slippery.

A Vehicle Vibration Control System by Active Control has been developed. The experimental results using a 4-cylinder gasoline engine installed in a car showed that at the position of the driver's seat, the acceleration of the vibration was reduced by 16 dB. This system operates stably and at low cost because of having a feedforward system, so many applications can be expected in the near future as methods for vehicle vibration reduction.

This paper proposes a new Electric Power Steering (EPS) control strategy that enables improvement to steering-wheel returnability. Using a conventional EPS controller, frictional loss torque in the steering mechanism reduces steering-wheel returnability, which drivers occasionally perceive as unpleasant. This phenomena occurs in any EPS system regardless of motor type or mounting location. To improve steering-wheel returnability for EPS-equipped vehicles, we developed a new control strategy based on estimation of alignment torque generated by tires and road surfaces. This proposed control strategy requires no supplemental sensors like steering-wheel angle or motor-angle sensors. We experimented with this proposed control algorithm using a test vehicle and confirmed that it enables improved steering wheel returnability and also better on-center feeling.

This paper proposes a new Electric Power Steering (EPS) control strategy that enables remarkable progress on steering maneuverability for stationary vehicles. Using a conventional controller, undesirable steering vibration prevented us from reducing steering torque. To eliminate this vibration, we developed a new control strategy based on damping for specified frequency using a motor angular-velocity estimator. We experimented with this proposed control algorithm using a test vehicle and confirmed that it enables reduced steering torque without any perceived vibration for drivers. Concerning the gradient of the assist-map, the proposed control strategy enabled more than three times higher compared with that of the same type vehicles on the market as the test vehicle. This proposed control strategy requires only the torque sensor signal, supply voltage and current to the motor, which are used in the conventional EPS systems, so no supplemental sensors are required.