H. Sado

Bio: H. Sado is an academic researcher from University of Tokyo. The author has contributed to research in topics: Electric motor & Electric vehicle. The author has an hindex of 2, co-authored 2 publications receiving 330 citations.

Motion control in an electric vehicle with four independently driven in-wheel motors

Abstract: We study methods of motion control for an electric vehicle (EV) with four independently driven in-wheel motors. First, we propose and simulate a novel robust dynamic yaw-moment control (DYC). DYC is a vehicle attitude control method that generates yaw from torque differences between the right and left wheels. The results of simulations, however, identify a problem with instability on slippery, low /spl mu/ roads. To solve this problem, a new skid detection method is proposed that will be a part of traction control system (TCS) for each drive wheel. The experimental results show that this method can detect a skidding wheel, without any information on chassis velocity. Therefore, this method will be of great help during cornering or braking in a TCS. These methods will be integrated and tested in our new experimental EV.

Anti-skid control with motor in electric vehicle

Abstract: Motor's fast torque response is one of the advantages of electric vehicles (EVs), and the advanced anti-skid control is included in this advantage. Simulation results show that the feedback gain of wheel velocity control can be high enough to suppress the serious skid, if the actuator delay is small enough. The dynamics of wheel can be changed with this control, and the driven wheel's inertia can be increased accordingly. Experiments results showed the effectiveness of this skid prevention method. This is the fast minor loop control of driven wheel, achieved only with the fast torque response of the electric motor. Thus the method can be used to maximize the advantage of EVs.

Future vehicle driven by electricity and Control-research on four-wheel-motored "UOT electric march II"

Abstract: The electric vehicle (EV) is the most exciting object to apply "advanced motion control" technique. As an EV is driven by electric motors, it has the following three remarkable advantages: 1) motor torque generation is fast and accurate; 2) motors can be installed in two or four wheels; and 3) motor torque can be known precisely. These advantages enable us to easily realize: 1) high performance antilock braking system and traction control system with minor feedback control at each wheel; 2) chassis motion control like direct yaw control; and 3) estimation of road surface condition. "UOT Electric March II" is our novel experimental EV with four in-wheel motors. This EV is made for intensive study of advanced motion control of an EV.

Lateral Stability Control of In-Wheel-Motor-Driven Electric Vehicles Based on Sideslip Angle Estimation Using Lateral Tire Force Sensors

Abstract: This paper presents a method for using lateral tire force sensors to estimate vehicle sideslip angle and to improve vehicle stability of in-wheel-motor-driven electric vehicles (IWM-EVs) Considering that the vehicle motion is governed by tire forces, lateral tire force measurements give practical benefits in estimation and motion control To estimate the vehicle sideslip angle, a state observer derived from the extended-Kalman-filtering (EKF) method is proposed and evaluated through field tests on an experimental IWM-EV Experimental results show the ability of a proposed observer to provide accurate estimation Moreover, using the estimated sideslip angle and tire cornering stiffness, the vehicle stability control system, making best use of the advantages of IMW-EVs with a steer-by-wire system, is proposed Computer simulation using Matlab/Simulink-Carsim and experiments are carried out to demonstrate the effectiveness of the proposed stability control system Practical application of lateral tire force sensors to vehicle control systems is discussed for future personal electric vehicles

Estimation of Sideslip and Roll Angles of Electric Vehicles Using Lateral Tire Force Sensors Through RLS and Kalman Filter Approaches

Abstract: Robust estimation of vehicle states (e.g., vehicle sideslip angle and roll angle) is essential for vehicle stability control applications such as yaw stability control and roll stability control. This paper proposes novel methods for estimating sideslip angle and roll angle using real-time lateral tire force measurements, obtained from the multisensing hub units, for practical applications to vehicle control systems of in-wheel-motor-driven electric vehicles. In vehicle sideslip estimation, a recursive least squares (RLS) algorithm with a forgetting factor is utilized based on a linear vehicle model and sensor measurements. In roll angle estimation, the Kalman filter is designed by integrating available sensor measurements and roll dynamics. The proposed estimation methods, RLS-based sideslip angle estimator, and the Kalman filter are evaluated through field tests on an experimental electric vehicle. The experimental results show that the proposed estimator can accurately estimate the vehicle sideslip angle and roll angle. It is experimentally confirmed that the estimation accuracy is improved by more than 50% comparing to conventional method's one (see rms error shown in Fig. 4). Moreover, the feasibility of practical applications of the lateral tire force sensors to vehicle state estimation is verified through various test results.

Fuzzy-logic applied to yaw moment control for vehicle stability

Abstract: In this paper, we propose a new yaw moment control based on fuzzy logic to improve vehicle handling and stability. The advantages of fuzzy methods are their simplicity and their good performance in controlling non-linear systems. The developed controller generates the suitable yaw moment which is obtained from the difference of the brake forces between the front wheels so that the vehicle follows the target values of the yaw rate and the sideslip angle. The simulation results show the effectiveness of the proposed control method when the vehicle is subjected to different cornering steering manoeuvres such as change line and J-turn under different driving conditions (dry road and snow-covered).