Abstract
This paper proposes the concepts of sliding mode schemes for fault tolerant control. The theoretical ideas developed in the paper were applied to a multi-motor electric vehicle (EV). To address this problem, we started by revisiting the modeling of vehicle dynamics focusing on nonlinear single-track model. The vehicle response to external perturbation forces, which are generated by unbalanced right and left traction forces due to malfunctions in motor drive, is described using the transfer functions analysis. The designing of a sliding mode controller for handling faults is described. The proposed scheme shows that certain motor drive failures can be handled directly without reconfiguring the controller. Simulation results obtained with CarSim vehicle model show the effectiveness of the fault tolerant control in various driving scenarios.

Abstract
Unknown input observers (UIO) can be used in the model-based fault diagnosis (FD) system to reduce or eliminate the effect of unknown disturbances present on the process and used to create a set of residuals that are decoupled and sensitive to faults. In this work, a new FD scheme of the In-Wheel motors electric vehicle (IWM-EV) with active front steering was carried out, as well as the design of the fault isolation banks of UIOs. These banks are used to generate residuals that are robust againts to noise and are sensitive to only one fault. This way the faults in the steering or in-wheel actuator are detected and isolated with a higher rate of accuracy. The proposed FD scheme is verified by Carsim® and Matlab/Simulink® cosimulation. © 2017 Taylor & Francis Group, London.

Abstract
The new vehicle platforms for electric vehicles (ENTs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control r strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as for as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.

Abstract
It is demonstrated that in grid-tied-inverter control, resonant integrators can be moved from the current loop to the input voltage filter allowing for better accuracy of voltage rms and frequency measurements whithout compromising controlability. Design of the input filter is discussed to ensure good performance and phase compensation and a robust feed-forward is built upon this filter that, together with the elimination of output distortion, results in a fair open-loop control response. By closing the loop with a PI controller and by turning off supposedly non-conducting IGBTs, a current transient results that competes with state-of-the-art control strategies and is only limited by output filter inductance while allowing for a fast and accurate estimator of grid parameters such as voltage rms and frequency, essential for fast droop control.

Abstract
This paper presents a study of the combined influence of battery models and sizing strategy for hybrid and battery-based electric vehicles. In particular, the aim is to find the number of battery (and super capacitor) cells to propel a light vehicle to run two different standard driving cycles. Three equivalent circuit models are considered to simulate the battery electrical performance: linear static, non-linear static and non-linear with first-order dynamics. When dimensioning a battery-based vehicle, less complex models may lead to a solution with more battery cells and higher costs. Despite the same tendency, when a hybrid vehicle is taken into account, the influence of the battery models is dependent on the sizing strategy. In this work, two sizing strategies are evaluated: dynamic programming and filter based. For the latter, the complexity of the battery model has a clear influence on the result of the sizing problem. On the other hand, a modest influence is observed when a dynamic programming strategy is followed.

Abstract
Modern electric vehicles are most often designed with actuator redundancy and in-wheel propulsion, a combination that appears particularly suitable for the design of motion controllers that can optimally blend multiple objectives, such as dynamic, safety and driver-oriented. This paper considers such a technological setting and concentrates on the design of a path-following algorithm with minimum-time features, with the aim of combining performance and energy-oriented optimization of the vehicle motion. Specifically, an approximate minimum-time trajectory is obtained by appropriate convexification of the resulting optimization problem. The effectiveness of the approach is assessed by means of simulation tests carried out on the CarSim vehicle simulation environment.