Abstract

Peak oil, climate change and the achievement of energy independence have set the world into a new energy transition seeking to decarbonize both the power generation and transportation sectors. The convergence and synergy between both sectors, an electrified transportation powered by renewable energy, holds true potential to significantly reduce the world’s dependence on fossil fuels and the consequent emission of greenhouse gases. Nonetheless the integration of electric vehicles on the power system is not a minor issue and its associated impacts need to be carefully analyzed and addressed. In this context the main objective of this thesis is to develop a smart charging solution to safely integrate Plug-in Electric Vehicles into low voltage distribution networks while mitigating their corresponding impacts. This is done by designing a control algorithm capable to simultaneously meet both voltage and thermal network constrains by managing the vehicle’s charging process in real-time, while at the same time being respectful to current charging standards, computationally light and implementable in any current radial distribution grid. The proposed charging algorithm is built under a “Multi-Agent System” architecture combining a local decentralized voltage management with a centralized thermal control conceived to minimize user impact under three alternative optimization techniques. The architecture is fully implemented and tested on a realistic environment using Simulink by modeling key elements such as the charging stations, the vehicles themselves, and the different dwellings. An extensive analysis of the algorithm’s performance is completed testing it under multiple relevant scenarios. Finally the control algorithm is transferred to a real-time simulator (dSPACE MicroLabBox) to be validated and further evaluate its behavior through hardware-in-the-loop (HIL) simulations using both real charging stations and Plug-in Electric Vehicles available in the laboratory A satisfactory validation of the algorithm’s execution under and compatibility with real hardware is revealed by the HIL tests. At the same time a successful management of the considered network voltage and thermal constrains is obtained under all implementations, causing a minimal impact over the participating users and effectively peak shaving their total aggregated demand. For a full vehicle penetration scenario, the proposed control successfully prevents over 200 voltage limit violations and achieves so while significantly reducing the total transformer loading deviation, almost halving it when compared to an equivalent unrestricted charging case, and ensuring a net zero impact to 95% of participating users under its most effective thermal implementation. The study also reveals that a full participation of all vehicle owners is not critical factor to ensure a proper grid operation under the designed algorithm, as satisfactory results are also obtained when only half of them are actively involved in network management. Finally an economic assessment covering the application of the designed control over conventional network reinforcements further demonstrates the advantages of such an active management approach reporting additional economic benefits to the DSO.

Abstract

The main objective of this project is to design a new gearbox for an electric Formula SAE car. The last car had one motor for each wheel, and for the new car, only one motor will be used to give traction to the rear wheels. The gear selection has been done by using the Optimum Lap software. Which after giving the main parameters of the car as well as the geometry of the circuit, returns the data needed to design the powertrain system, among others. A comparison haas been done between the different transmission systems available. After deciding that the use of a gearbox is the best option, another comparison has been done to choose the type of gears. To do so three different basic designs have been done with CATIAV5. The selected option is to use three stage spur gears. To design the tooth form, materials and shaft-hub conection selection, the KISSSOFT software has been used. To optimize the different parts after designing them with CATIAV5, the parts have been meshed with HyperMesh and processed in Abaqus. The final design weights less than 6kg and contains all the parts needed inside of the gearbox. The connections to the motor or the wheels have not been designed.

Abstract

Novo Mesto is a small town in the Slovenian countryside which is undergoing a new project of road safety. New traffic signals are to be placed in bus stops to give drivers awareness of children standing waiting for the bus. Our mission is to use an eye tracker (the Dikablis device by Ergoneers) to study the reaction of three test drivers against these new signals; if they do detect them or not and if they modify their driving behavior once noticed them. The methodology is to do a first test before the signal placements and another one after, and afterwards compare both situations. Results are satisfying, with high values of reliability, and make us think the new signals will be useful and will contribute to make the road a safer place for children. Outgoing

Abstract

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works This paper proposes a charging/discharging process for electric vehicles according to mode 4, specifically based on the CHAdeMO protocol. These initiatives will enable acceptably fast charging of EVs. The proposal has been designed and implemented within the Endesa Novare Vehicle to Microgrid project. As a first stage of the project, the charge/discharge process has been emulated before it will be developed in a real device. The emulation consists of two main parts: (i) an electric vehicle and its battery management system emulated by a microcontroller, and (ii) a charging/discharging device emulated by a computer application. Both parts communicate via CAN bus as it is done in existing protocols. The proposed control flow for charging and discharging and the results of the emulation are presented. Moreover, in order to be able to manage charge and discharge processes according to power network operator, a data model for both electrical vehicle and charging/discharging device according to standard IEC 61850-7-420 is also proposed. Document type: Conference object

Abstract

This paper presents an energy-based model of a series hybrid electric vehicle. The proposed propulsion system has a new configuration using a wound-rotor synchronous generator (WRSM) and a doublyfed induction machine (DFIM). From the classic dq dynamical equations of the WRSM and DFIM the port-controlled Hamiltonian models of each machine is described. One of the abilities of the port-based models is that the complete model is easy to obtain by means of interconnection rules. Following this, the Hamiltonian model of the whole system is obtained. Similarly, the bond graph approach allows to build a complex model by interconnecting several subsystems. This paper also contains bond graph models of the machines and the propulsion system. Numerical simulations are also presented in order to validate the proposed models. Peer Reviewed

Abstract

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works Electric vehicles (EVs) could become a controllable grid load by using demand side management techniques, but this requires an information and communications technology (ICT) infrastructure and aggregator agents, to coordinate the EV charging process. To determine the opportunity cost of aggregators, it is necessary to analyze the extra charges in the electricity market, due to the EV charging demand. The EV energy consumption is modeled following agent-based techniques, and the data used corresponds to the Iberian day-ahead market and Spanish mobility needs in 2012. The simulation results show that EVs would significantly influence the electricity price on the day-ahead market, depending on the EV charging behavior.