Roger Graaf

Active Fault-Tolerant Control for Electric Vehicles With Independently Driven Rear In-Wheel Motors Against Certain Actuator Faults

An active fault-tolerant control (AFTC) system is proposed in this paper for electric vehicles with independently driven in-wheel motors (IWMs). It comprises a baseline controller, a set of reconfigurable controllers, a fault detection and diagnosis (FDD) mechanism, and a decision mechanism. The baseline controller, which is actually a passive fault-tolerant controller, is applied to accommodate actuator faults and stabilize the faulty vehicle when the actuator fault occurs. After the fault is detected and estimated by the FDD mechanism, a proper reconfigurable controller is switched ON to achieve optimal postfault performance. Taking advantage of the robust gain-scheduling algorithm, the loss-of-effectiveness and additive faults of the IWMs can be accommodated by the baseline controller, and the estimation error of the FDD mechanism can be tolerated by the reconfigurable controllers. The results of simulations in CarSim and vehicle experimental tests show the effectiveness of this AFTC system in dealing with certain IWM faults.

Beobachtung von Fahrzeugzuständen der Querdynamik mit integrierter reibwertschätzung

Regelungssysteme fur die Fahrdynamik beruhen auf Informationen uber den aktuellen Fahrzeugzustand. Wahrend viele Daten direkt aus Sensorsignalen gewonnen werden konnen, lassen sich wichtige Grosen wie die Fahrzeugquergeschwindigkeit und der zugehorige Strasenreibwert nicht mit der vorhandenen Sensorik erfassen und mussen uber einen Beobachteransatz ermittelt werden. Diese Zustandsschatzung wurde in mehreren Projekten zur integrierten Fahrdynamikregelung am Ford-Forschungszentrum in Aachen erfolgreich eingesetzt.

Fault-type identification and fault estimation of the active steering system of an electric vehicle in normal driving conditions

Fault-type identification and fault estimation for the active steering system of a vehicle are considered in this paper. The vehicle studied is an electric ground vehicle, which operates mainly under normal driving conditions. First, a two-degree-of-freedom dynamic model of the lateral motion and the yaw motion of the vehicle is established and verified by experimental data. Then, an adaptive observer is proposed to estimate the steering motor fault by using measurements of the yaw rate of the vehicle. Residuals are defined for specific fault-type identification purposes. Experimental tests on the electric ground vehicle are carried out to assess the fault identification and estimation performance as well as to reveal the limitations of and possible improvement in the proposed method.

Robust vehicle longitudinal motion control subject to in-wheel-motor driving torque variations

Driving torque variation which introduces external yaw moment greatly impacts vehicle motion particularly for distributed powertrain vehicles such as in-wheel motor electric vehicles. This paper proposes a weighted gain-scheduling H∞ controller to compensate for torque variation and track desired vehicle motions. The weighted H∞ performance is adopted to attenuate the effect of torque variation. A weighting factor is designed to tune the relative importance of external input and torque variation. An eigenvalue placement technique is used to confine the feedback control gain in certain region. The state feedback control gain is calculated by solving a minimization problem. Furthermore, a gain-scheduling scheme is used to incorporate time-varying signals in the system. Simulation studies were conducted on a high-fidelity vehicle model developed in CarSim®. Results indicate that the designed controller is able to compensate for driving torque variation and track the desired vehicle trajectory simultaneously.

Actuator Fault Sensitivity Analysis for In-Wheel Motor Electric Ground Vehicle With Active Steering System

This paper presents the sensitivity analyses on vehicle motions with regard to faults of in-wheel motors and steering motor for an electric ground vehicle (EGV) with independently actuated in-wheel rear motors. Based on the vehicle model, direct method is applied to determine, to what extent, that different actuator faults affect vehicle motions such as the longitudinal velocity, lateral velocity, and yaw rate. For motion indices like vehicle sideslip angle and longitudinal acceleration, linearizations around equilibrium points are conducted and their sensitivities to actuator faults are analyzed. Results show that all mentioned vehicle motions are more sensitive to the fault of steering motor than that of in-wheel motors. In addition, the effects on vehicle motions due to four types of faults, i.e. additive, loss-of-effectiveness, time-varying-gain and stuck-at-fixed-level faults, are examined through CarSim® simulations and vehicle experiments under a representative maneuver.Copyright

State estimation of the vehicle lateral dynamic with integrated estimation of the friction between tyre and road

Control systems for vehicle stability require information about the actual vehicle state. While many states can be obtained from sensor signals, some important states, like the lateral velocity and the corresponding tyre-road friction have to be reconstructed by a vehicle state estimator, comprising of a simplified vehicle model. The efficiency of the developed vehicle state estimator has been proven in several projects for integrated vehicle dynamics control at the Ford Research Centre in Aachen.