\chapter{Introduction}
\section{Motivation}
Nowadays the number of personal cars is still growing and the most used internal combustion engines (ICE) cause serious problems for the environment and hydrocarbon resources. One of the biggest recent deals is thus to develop vehicles with alternative power sources.

A variety of different Hybrid Electric Vehicles (HEV) was introduced and even incorporated to the market. Even though these solutions succeeded to decrease notably the fuel consumption, the ICE still plays the main power source role in these systems. The demands are higher and higher and that is why the full electric vehicle (EV) is being developed.

The EV has many advantages over the conventional internal combustion engine vehicle, such as absence of actual emissions, high efficiency, independence from petroleum, and quiet and smooth operation. Especially the ecological aspects motivate the EV development. In the case of higher market share by EV in the future, the electricity making process should be examined to accomplish the pollution reduction goal. 

The development of new batteries slowed down in the last years and even though some new technologies appeared, the specific energy and power are not as high as foreseen. The battery is one of the most important parts of EV and acts as the primary energy source. That is why it is very important to develop a sophisticated energy management system allowing the optimal energy consumption and recuperation.

\section{Objectives}
In the past decades, a vehicle modelling was studied in detail so the mathematical models and approximations can be found easily. The next step in the automotive industry was to improve the vehicle driving capabilities using a special control systems usually embedded in micro-controllers which developed very rapidly during the past years. Also, the new processors calculation power enables the use of real-time control and optimization algorithms. 

Even though many optimization algorithms were already examined, this work introduces new technologies and new approaches to the energy optimization. It is proposed to use super-capacitors in addition to batteries to support them and recuperate energy from regenerative breaking. The goal of energy management is to optimise the power-split-ratio (PSR) between batteries and super-capacitors, because the super-capacitors can mostly provide energy with higher efficiency, but can not store enough of it.

The energy management is based on the idea described in~\cite{bin10}. In the first time, the geographic 3D data of the driving cycle are obtained and depending on the predicted velocity profile, the driving power profile is predicted. Finally, the PSR is optimised for this power profile using either dynamic programming algorithm introduced in~\cite{bin10} or our self-made algorithm. This algorithms were developed to be independent on a concrete vehicle and components parameters so they could be used in any EV with batteries and super-capacitors.

In the first part, this work summarises vehicle general model description and introduces a formula for vehicle power calculation. Different EV topologies are shown. Also the EV components and their mathematical models are presented. In the next section, some energy optimization methods and problems are discussed and optimization algorithms principles, simulations and comparisons are shown. Furthermore, the Java implementation of this algorithms is clarified. In the last part, the prototype of EV energy optimization application for Android operating systems is presented.

