Abstract
The design of high performance induction motor drives is a complex task, and the every day compelling requirements in energy efficiency and performance assumes the motivation on finding a more integrated solution on implementing induction motor control. The main subjects of this paper are two: to discuss the IFOC one-chip solution and to explore the development of simple graphical applications in order to operate this control in a simple and effective way. Experimental results are presented to illustrate the main points of our paper.

Abstract
This paper is concerned with design considerations and tradeoffs involved in the power electronics development for light electric vehicles. A review of propulsion system design, power conversion structure and control is presented. A three-phase squirrel-cage induction motor is used as propulsion system for an electric scooter. The motor is controlled at different operating conditions by means of a simple scalar control using a low cost controller board developed for light electric vehicles used in local areas. Experimental results show that the proposed digital controller is able to follow the reference speed with a suitable dynamics for the electric scooter.

Abstract
This paper presents and proposes a new approach to achieve robust speed estimation in induction motor sensorless control. The estimation method is based on a reduced-order Extended Kalman Filter (EKF), instead of a full order EKF. The EKF algorithm uses a reduced-order statespace model structure that is discretized in a particular and innovative way proposed in this paper. With this model structure, only the rotor flux components are estimated, besides the rotor speed itself. Important practical aspects and new improvements are introduced that enable us to reduce the execution time of the algorithm without difficulties related to the tuning of covariance matrices, since the number of elements to be adjusted is reduced.

Abstract
Battery-powered electric vehicle appear to be one of the viable solutions for the growing concerns for environmental protection and the fast rate of depletion of world fuel oil supply. This type of vehicle can become a viable alternative to the internal combustion engine only if they are able to meet certain reliability, safety, performance, and cost criteria. In addition, this type of electrical vehicles have serious disadvantages because of the limitation on cruising range imposed by weight, capacity of the electric accumulators and long recharging time. Improvement of efficiency of induction motor traction drives is an important issue in pure electric vehicles to improve the running distance on one charge. In this paper, the authors evaluate a loss-minimization algorithm (LMA) by considering their influence on the performance of the vehicle. The evaluation of the proposed LMA is demonstrated experimentally under different operating conditions of the vehicle.

Abstract
The purpose of this paper is to design the propulsion system for a Neighbourhood Electric Vehicle (NEV) and implement a control architecture which is suitable for this kind of application. The review of the vehicle model is presented. This model is used to establish the propulsion system requirements in terms of torque and power. Once these are known the specifications for the motor and transmission system are derived. A digital platform has been developed and implemented. This hardware platform interacts via wireless communication with a high level application to facilitate writing and reading the host registers. A PC graphical user interface was developed to allow the computation of the control parameters. Some experimental results are provided in order to verify the performance of this new controller.

Abstract
This paper presents FIEEV - Fault Injection Environment for Electric Vehicles, a Matlab/Simulink-based simulator environment for evaluating the fault impacts on vehicle stability in electrical vehicles. FIEEV makes it possible to simulate the temporal behavior of the faults and to study its effects on loss of vehicle's performance. Simulation results are presented to prove the validity of the presented framework. © 2012 IEEE.