Energy Management System For Three-Wheel Light Electric Vehicle Using Multi-Sources Energy Models

Hybrid electric vehicles, plug-in hybrid electric vehicles, battery electric vehicles, fuel-cell vehicles are just a few technologies that are being researched worldwide today. Applying renewable energy such as battery, fuel cell and super-capacitor in the electric vehicle is a smart and ideal solution. However, battery as a single-source in electric vehicle has many disadvantages such as limited travel distance and longer charging time. Besides, battery reduces its electrical characteristics through high current flow, high temperature, self-discharge and low battery capacity level. Fuel cell has low power response during sudden energy demand and requires an expensive infrastructure for refueling. In case of light fuel cell vehicle, small tank is practical for exchange tank. In super-capacitor side, it cannot support enough energy for a single powered electric vehicle purposes, however can be used as secondary power supply. Thus, an intelligent energy management system (EMS) of various sources is necessary to counterbalance the drawback of the sources. To solve the problem, the objective of the research is to develop an intelligent EMS which can conduct multi-sources for three wheel light electric vehicle (LEV). A rule-based control algorithm which contains eight states in EMS is designed to control power switches and to ensure sufficient energy is delivered to the load. The work of this research begins by electrical analysis in PSPICE simulation which focuses in circuit design and testing the state condition. A close loop vehicle system implemented with intelligent EMS is designed in MATLAB/Simulink. The simulation model is simulated with a real three wheel scooter specification which has capacity of 5.4 kW DC machine. To show effectiveness of the developed vehicle system, the performance and efficiency of the vehicle simulation is compared with standard drive cycle such as ECE-47 and ECE-15. To justify the simulation model, a scaled-down lab test bench model is designed using dSPACE DS 1104. The LEV model with 18 W load power is implemented in the developed test bench prototype. As a result, the vehicle system specification for the lab test bench model is reduced accordingly to the ratio of load power. The power specifications of the multi-source models such as 30 W for fuel cell, 3 Ah for rechargeable sealed lead acid battery and 100F for super-capacitors have been used. An EMS hardware is designed to offer a bridge between MATLAB/Simulink and dSPACE DS 1104. In the EMS hardware design, the switching relay is used for selection of the sources and current transducers which are used for measuring load current and battery capacity. All input and output signals from the EMS hardware design are connected to the dSPACE DS 1104 for data presentation in graphical user interface. For the uphill simulation test, using ECE-47 drive cycle, multi-source energy models shows that the power effectiveness is 94.6% where as for the battery, as a single-source, it is 84.9%. The lab test bench model also proved that in extension of 33% of speed ECE-47 drive cycle, the energy efficiency of multi-source LEV is 80.2% which is better performance than that of combustion engine energy efficiency of 29.2%. Therefore, the system equipped with an intelligent control algorithm has promising potential in vehicle energy management applications for the future

Intelligent transportation systems for electric vehicles

Electric Vehicles market penetration is increasing, transforming transportation, creating 8 synergies among energy and transportation. From initial blockers, like purchase price, range, charging time, lifetime, and safety are all battery-driven handicaps. In this context smart energy management system plays an important role, where intelligent process plays an important role. This review akes into account the special issue dedicated to this topic at the end of 2018, try to identify major work performed in the last 3 years and identify major topics for the upcoming years.info:eu-repo/semantics/publishedVersio

Electric road vehicles - overview, concepts and research at Reutlingen university

The paper details the architecture of fully electrified vehicles as well as their new electronic systems. Examples of up-to-date electrical passenger cars are given. A very important question, that is the environmental foot-print of electrical vehicles compared to conventional ones, is examined. A research project is introduced where a fleet of two-wheeled vehicles is available for day-to-day use. Research on vehicles, software for fleet management and battery range prediction is described.В данной статье привeдены подробные сведения о принципе работы электрифицированных транспортных средств, а также описаны их новые электрические системы. Показан примеры уже существующих электрических пассажирских транспортных средств. Рассмотрено влияние электрифицированного транспорта на окружающую среду в сравнении с обычными видами транспорта. Приведен проект исследований, в рамках которого для ежедневного использования существует парк двух колесных электрифицированных транспортных средств. Описаны исследования, непосредственно связанные с электрифицированным транспортом, определением точного времени разряда батареи, а также программным обеспечением, позволяющим управлять парком таких транспортных средств.У статті наведено докладні відомості щодо принципів роботи електрифікованих транспортних засобів, а також описано їх нові електричні системи. Показано приклади вже існуючих електричних пасажирських транспортних засобів. Розглянуто вплив електрифікованого транспорту на навколишнє середовище у порівнянні із звичайними видами транспорту. На- ведено проект досліджень, у рамках якого існує парк двоколісних електрифікованих транспортних засобів для щоденного використання. Описано дослідження, безпосередньо пов'язані із електрифікованим транспортом, визначенням точного часу розряду батареї, а також програмним забезпеченням, що дозволяє керувати парком таких транспортних засобів

An investigation on the effect of driver style and driving events on energy demand of a PHEV

Environmental concerns, security of fuel supply and CO2 regulations are driving innovation in the automotive industry towards electric and hybrid electric vehicles. The fuel economy and emission performance of hybrid electric vehicles (HEVs) strongly depends on the energy management system (EMS). Prior knowledge of driving information could be used to enhance the performance of a HEV. However, how the necessary information can be obtained to use in EMS optimisation still remains a challenge. In this paper the effect of driver style and driving events like city and highway driving on plug in hybrid electric vehicle (PHEV) energy demand is studied. Using real world driving data from three drivers of very different driver style, a simulation has been exercised for a given route having city and highway driving. Driver style and driving events both affect vehicle energy demand. In both driving events considered, vehicle energy demand is different due to driver styles. The major part of city driving is reactive driving influenced by external factors and driver leading to variation in vehicle speed and hence energy demand. In free highway driving, the driver choice of cruise speed is the only factor affecting vehicle energy demand

Eras of electric vehicles: electric mobility on the Verge. Focus Attention Scale

Daily or casual passenger vehicles in cities have negative burden on our finite world. Transport sector has been one of the main contributors to air pollution and energy depletion. Providing alternative means of transport is a promising strategy perceived by motor manufacturers and researchers. The paper presents the battery electric vehicles-BEVs bibliography that starts with the early eras of invention up till 2015 outlook. It gives a broad overview of BEV market and its technology in a chronological classification while sheds light on the stakeholders’ focus attentions in each stage, the so called, Focus-Attention-Scale-FAS. The attention given in each era is projected and parsed in a scale graph, which varies between micro, meso, and macro-scale. BEV-system is on the verge of experiencing massive growth; however, the system entails a variety of substantial challenges. Observations show the main issues of BEVsystem that require more attention followed by the authors’ recommendations towards an emerging market