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Steer-by-wire (SBW) systems benefit from several advantages including lower weight, volume, and cost compared to counterpart electric power steering systems. However, system reliability is impacted since SBW performance is highly dependent on correct operation of several voltage, current, speed, yaw rate, and position sensors. This paper presents a new method in SBW system reliability improvement by introducing a novel fault detection, isolation, and reconstruction (FDIR) control technique. The proposed FDIR method detects if any fault is observed on voltage or current sensors and identifies the faulty sensor location. Additionally the identified faulty sensor's output is replaced with an estimated value to allow system continuous fault-ride through operation. The SBW system equipped with proposed FDIR technique provides fault-tolerance property against up to 3 faulty voltage or current sensors. Therefore, enhanced overall reliability is obtained at no further hardware costs associated with additional sensors redundancy solutions. The proposed technique is studied using system modelling and hardware prototyping, and its effectiveness is demonstrated using simulation and experimental results. [ABSTRACT FROM AUTHOR]

While steer-by-wire (SBW) systems benefit from improved performance and comfort, they require a large number of sensors impacting whole system reliability. In order to address this challenge fault tolerance property against sensor faults has to be improved. Application of redundancy for the sensors is the best solution proposed so far. This paper proposes a novel solution of analytical redundancy based on various position estimation methods for both electrical motor and steering wheel position sensors. Three different estimation techniques including extended programmable cascaded low-pass filter (EPCLPF), stator flux linkage estimator using stator currents, as well as stator flux linkage estimator using stator voltages are proposed for this purpose. The faulty sensors are recognized using a voting technique in which a comparison between the sensors' outputs with the estimated values is made. In this way, the SBW system reliability is highly improved with no additional cost and space. Simulation and experimental results are presented to confirm the presented fault tolerant SBW system capabilities. [ABSTRACT FROM AUTHOR]