Energy Storage Systems for Electric Vehicles: Performance Comparison based on a Simple Equivalent Circuit and Experimental Tests

The decision to select the most suitable type of energy storage system for an electric vehicle is always difficult, since many conditionings must be taken into account. Sometimes, this study can be made by means of complex mathematical models which represent the behavior of a battery, ultracapacitor or some other devices. However, these models are usually too dependent on parameters that are not easily available, which usually results in nonrealistic results. Besides, the more accurate the model, the more specific it needs to be, which becomes an issue when comparing systems of different nature. This paper proposes a practical methodology to compare different energy storage technologies. This is done by means of a linear approach of an equivalent circuit based on laboratory tests. Via these tests, the internal resistance and the self-discharge rate are evaluated, making it possible to compare different energy storage systems regardless their technology. Rather simple testing equipment is sufficient to give a comparative idea of the differences between each system, concerning issues such as efficiency, heating and self-discharge, when operating under a certain scenario. The proposed methodology is applied to four energy storage systems of different nature for the sake of illustration.

Dietary Fibre in Pig's Diets: Effects on Greenhouse Gas Emissions from Slurry Storage to Field Application

Pig’s slurry is a key source of greenhouse gases (GHG). In Spain, GHG emissions (CH4+ N2O) from pig slurry (storage and land application) accounted in 2011 for 18.4% of total GHG emissions (in CO2- equivalent) of the agriculture sector according to the National Inventory Report (NIR). Slurry composition can be modified through diet manipulation. The aim of this work was to evaluate the effect of different fibre types in fattening pigs’ diets on GHG emissions from pig slurry storage and field application.

Reducing the impact of EV charging on the electric grid

One of the main objectives of European Commission related to climate and energy is the well-known 20-20-20 targets to be achieved in 2020: Europe has to reduce greenhouse gas emissions of at least 20% below 1990 levels, 20% of EU energy consumption has to come from renewable resources and, finally, a 20% reduction in primary energy use compared with projected levels, has to be achieved by improving energy efficiency. In order to reach these objectives, it is necessary to reduce the overall emissions, mainly in transport (reducing CO2, NOx and other pollutants), and to increase the penetration of the intermittent renewable energy. A high deployment of battery electric (BEVs) and plug-in hybrid electric vehicles (PHEVs), with a low-cost source of energy storage, could help to achieve both targets. Hybrid electric vehicles (HEVs) use a combination of a conventional internal combustion engine (ICE) with one (or more) electric motor. There are different grades of hybridation from micro-hybrids with start-stop capability, mild hybrids (with kinetic energy recovery), medium hybrids (mild hybrids plus energy assist) and full hybrids (medium hybrids plus electric launch capability). These last types of vehicles use a typical battery capacity around 1-2 kWh. Plug in hybrid electric vehicles (PHEVs) use larger battery capacities to achieve limited electric-only driving range. These vehicles are charged by on-board electricity generation or either plugging into electric outlets. Typical battery capacity is around 10 kWh. Battery Electric Vehicles (BEVs) are only driven by electric power and their typical battery capacity is around 15-20 kWh. One type of PHEV, the Extended Range Electric Vehicle (EREV), operates as a BEV until its plug-in battery capacity is depleted; at which point its gasoline engine powers an electric generator to extend the vehicle's range. The charging of PHEVs (including EREVs) and BEVs will have different impacts to the electric grid, depending on the number of vehicles and the start time for charging. Initially, the lecture will start analyzing the electrical power requirements for charging PHEVs-BEVs in Flanders region (Belgium) under different charging scenarios. Secondly and based on an activity-based microsimulation mobility model, an efficient method to reduce this impact will be presented.