Abstract
In this paper we present an electric go-kart suitable for an instructional laboratory in electric drives. An overview of propulsion system design, power conversion structure and control is presented. A three-phase squirrel-cage induction motor is used as propulsion system. 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. The prototype has been designed specifically to meet the requirement of low cost and it contains all of the active functions required to implement the control of the go-kart.

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
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
For a long time, controlling AC motors in an efficient way, was a task only in the reach of some very specific electronic design Engineers. Now, with the up rise of Integrated Platforms it is possible to implement, with almost no effort, the desired application, customizing almost everything at the reach of a simple and user friendly software interface. However, the simplicity in control and monitoring has a major settle back. As expected, such products, very desirable by the market, are only sold in conjunction with an evaluation platform. Sometimes this platform does not fit the consumer needs and buying the full package is not a satisfactory solution, especially if it is just to get the control and monitoring software. In this paper, it will be shown that low cost alternatives are possible. Using free tools and manufacturer's documentation, it is simple to implement Motor Control with the desired IC by means of a very intuitive and complete Graphical Unit Interface (GUI), built attending our special needs.

Abstract
Factors such as uncertainty associated to fuel prices, energy demand and generation availability, are on the basis of the agents major concerns in electricity markets. Facing that reality, price forecasting has an increasing impact in agents' activity. The success on bidding strategies or on price negotiation for bilateral contracts is directly dependent on the accuracy of the price forecast. However, taking decisions based only on a single forecasted value is not a good practice in risk management. The work presented in this paper makes use of artificial neural networks to find the market price for a given period, with a certain confidence level. Historical information was used to train the neural networks and the number of neural networks used is dependent of the number of clusters found on that data. K-Means clustering method is used to find clusters. A study case with real data is presented and discussed in detail.

Abstract