4,127 research outputs found

    Smart Procurement Of Naturally Generated Energy (SPONGE) for PHEV's

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    In this paper we propose a new engine management system for hybrid vehicles to enable energy providers and car manufacturers to provide new services. Energy forecasts are used to collaboratively orchestrate the behaviour of engine management systems of a fleet of PHEV's to absorb oncoming energy in an smart manner. Cooperative algorithms are suggested to manage the energy absorption in an optimal manner for a fleet of vehicles, and the mobility simulator SUMO is used to show simple simulations to support the efficacy of the proposed idea.Comment: Updated typos with respect to previous versio

    Electric vehicle possibilities using low power and light weight range extenders

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    Electric cars have the disadvantage of a limited range, and drivers may experience a range anxiety. This range anxiety can be solved by adding a range extender. But, the range extender should be light so as not to significantly increase the weight of the original vehicle. In urban areas with dense traffic (usually developing countries), the average speed around cities is typically lower than 50km/h. This means, the rolling resistance losses are more important than aerodynamic losses, and a weight reduction results in a bigger electrical range. Therefore, smaller and lighter range extenders are of much interest. The contribution of this paper is to indicate the possibility of range extenders with less than 25 kg with a capacity of 150 to 200 cc to suit a condition where weight counts. In this paper, the cost, environmental and grid impacts of going electric are also discussed. The effect of high altitude and driving style on the performance of an electric vehicle is assessed. The challenges and opportunities of vehicle electrification between countries with decarbonated power generation and fossil fuel dominated power generation are highlighted. Throughout the article, the case of Ethiopia is taken as an example

    Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-in Hybrid Electric Buses

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    We discuss a recently introduced ECO-driving concept known as SPONGE in the context of Plug-in Hybrid Electric Buses (PHEB)'s.Examples are given to illustrate the benefits of this approach to ECO-driving. Finally, distributed algorithms to realise SPONGE are discussed, paying attention to the privacy implications of the underlying optimisation problems.Comment: This paper is recently submitted to the IEEE Transactions on Automation Science and Engineerin

    Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

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    Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid

    Ready to Roll?: Overview of Challenges and Opportunities

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    Alternative Fuel Vehicles (AFVs) use combinations of vehicle fuels and technologies to reduce the use of petroleum in on-road vehicles. These include low-carbon fuels (sometimes blended with petroleum), electricity, and hybrid technologies combining internal combustion engines with electric motors. DVRPC's Ready to Roll? Report provides an overview for policymakers and citizens in the Greater Philadelphia region about the challenges and opportunities for expanded use of alternative fuel vehicles. The AFVs covered in this report include those most widely available today or likely to become available in the next 10 to 20 years

    Charging Scheduling of Electric Vehicles with Local Renewable Energy under Uncertain Electric Vehicle Arrival and Grid Power Price

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    In the paper, we consider delay-optimal charging scheduling of the electric vehicles (EVs) at a charging station with multiple charge points. The charging station is equipped with renewable energy generation devices and can also buy energy from power grid. The uncertainty of the EV arrival, the intermittence of the renewable energy, and the variation of the grid power price are taken into account and described as independent Markov processes. Meanwhile, the charging energy for each EV is random. The goal is to minimize the mean waiting time of EVs under the long term constraint on the cost. We propose queue mapping to convert the EV queue to the charge demand queue and prove the equivalence between the minimization of the two queues' average length. Then we focus on the minimization for the average length of the charge demand queue under long term cost constraint. We propose a framework of Markov decision process (MDP) to investigate this scheduling problem. The system state includes the charge demand queue length, the charge demand arrival, the energy level in the storage battery of the renewable energy, the renewable energy arrival, and the grid power price. Additionally the number of charging demands and the allocated energy from the storage battery compose the two-dimensional policy. We derive two necessary conditions of the optimal policy. Moreover, we discuss the reduction of the two-dimensional policy to be the number of charging demands only. We give the sets of system states for which charging no demand and charging as many demands as possible are optimal, respectively. Finally we investigate the proposed radical policy and conservative policy numerically
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