Abstract-This paper presents system modeling, analysis, and simulation of an electric vehicle (EV) with two independent rear wheel drives. The traction control system is designed to guarantee the EV dynamics and stability when there are no differential gears. Using two in-wheel electric motors makes it possible to have torque and speed control in each wheel. This control level improves EV stability and safety. The proposed traction control system uses the vehicle speed, which is different from wheel speed characterized by a slip in the driving mode, as an input. In this case, a generalized neural network algorithm is proposed to estimate the vehicle speed. The analysis and simulations lead to the conclusion that the proposed system is feasible. Simulation results on a test vehicle propelled by two 37-kW induction motors showed that the proposed control approach operates satisfactorily.

Abstract-This paper proposes a strategy to minimize the losses of an induction motor propelling an electric vehicle (EV). The proposed control strategy, which is based on a direct flux and torque control scheme, utilizes the stator flux as a control variable, and the flux level is selected in accordance with the torque demand of the EV to achieve the efficiency-optimized drive performance. Moreover, among EV's motor electric propulsion features, the energy efficiency is a basic characteristic that is influenced by vehicle dynamics and system architecture. For this reason, the EV dynamics are taken into account. Simulation tests have been carried out on a 1.1-kW EV induction motor drive to evaluate the consistency and the performance of the proposed control approach.

Abstract-This paper proposes a strategy to minimize the losses of an induction motor propelling an electric vehicle (EV). The proposed control strategy, which is based on a direct flux and torque control scheme, utilizes the stator flux as a control variable, and the flux level is selected in accordance with the torque demand of the EV to achieve the efficiency-optimized drive performance. Moreover, among EV's motor electric propulsion features, the energy efficiency is a basic characteristic that is influenced by vehicle dynamics and system architecture. For this reason, the EV dynamics are taken into account. Simulation tests have been carried out on a 1.1-kW EV induction motor drive to evaluate the consistency and the performance of the proposed control approach.

This paper presents system analysis, modeling and simulation of an Electric Vehicle (EV) with three different control strategies: Field Oriented Control (FOC), Direct Torque Control (DTC), and DTC using Space Vector Modulation (DTC-SVM). The objective is to assess the control strategy impact on the EV efficiency taking into account the vehicle dynamics. Indeed, among EV motor electric propulsion features, the energy efficiency is a basic characteristic that is influenced by vehicle dynamics and system architecture. Simulation tests have been carried out on a 37-kW EV that consists in an induction motor with a three-level IGBT inverter. Preliminary results seem to indicate that the DTC-SVM scheme is the best candidate.

The use of an Electric Differential (ED) constitutes a technological advance in vehicle design along with the concept of more electric vehicles. EDs have the advantage of replacing loose and heavy mechanical differentials and transmissions with lighter and smaller electric motors directly coupled to the wheels via a single gear or an in-wheel motor. This paper deals then with an Electric Differential System (EDS) for an Electric Vehicle (EV) directly driven by dual induction motors in the rear wheels. A sensorless control technique is preferred to a position or speed encoder-based control one to reduce the overall cost and to improve the reliability. The EDS main feature is the robustness improvement against system uncertainties and road conditions. The EDS control performances are validated through experiments on a dSPACE-based test bench. The experimental results show that the proposed controller is able to track the speed reference and the curvature angle with good static and dynamic performances.