A fault detection and diagnosis (FDD) algorithm of 4WID/4WIS Electric Vehicles has been proposed in this study aiming to find the actuator faults. The 4WID/4WIS EV is one of the promising architectures for electric vehicle designs which is driven independently by four in-wheel motors and steered independently by four steering motors. The 4WID/4WIS EVs have many potential abilities in advanced vehicle control technologies, but diagnosis and accommodation of the actuator faults becomes a significant issue.The proposed FDD approach is an important part of the active fault tolerant control (AFTC) algorithm. The main objective of the FDD approach is to monitor vehicle states, find the faulty driving motor and then feedback fault information to the controller which would adopt appropriate control laws to accommodate the post-fault vehicle control system.The unique character of the proposed FDD approach is that it is a system-level method, namely it tries to locate the faulty motor and motor driver systems, while it does not need to identify which part of the motor and motor driver systems has a failure. The information about which motor and motor driver system is faulty is total enough for the fault tolerant control mechanism which is also on the system level.The theoretical basis of the FDD method is the vehicle dynamics which demonstrate the relationship between the forces acted on the vehicle and the vehicle motions. The Analytical Redundancy Relations (ARR) method is applied to set up the residual generation equation. If a component fails in the motor and motor driver system, it causes the inconsistency in the vehicle dynamics relationship whose appearance is that the generated residuals are much larger than the thresholds. Based on this method, we can identify whether the motor and motor driver system is faulty or not. In order to obtain the residual generation equation, the magic formula tire model is adopted.Several simulations have been conducted to verify the proposed FDD approach. The results have shown that once the driving motor fails, the FDD approach identifies the fault and transfer this information to the FTC controller.