Optimizing EV driving-recharge time ratio a under limited grid connection

Tsirinomeny, Martel; Hõimoja, Hardi; Rufer, A.; Dziechciaruk, Grzegorz; Vezzini, Andrea

doi:10.1049/cp.2014.0400

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…The possibility of reducing the charging time is therefore linked, on the one hand, to the increase in the maximum power of supply of the charging point, and on the other hand to the increase in the maximum charging current of the battery without reducing the useful life cycles [70,71]. However, the excessive increase of the installed power in a charging point leads to an unjustified increase in the installation and maintenance costs of the plant as a function of the reduction in recharge time.…”

Section: Charging Interfacementioning

confidence: 99%

Overview of Main Electric Subsystems of Zero-Emission Vehicles

Dannier¹

2019

Propulsion Systems

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The rapid growth of the electric vehicle market has stimulated the attention of power electronics and electric machine experts in order to find increasingly efficient solutions to the demands of this application. The constraints of space, weight, reliability, performance, and autonomy for the power train of the electric vehicle (EV) have increased the attention of scientific research in order to find more and more appropriate technological solutions. In this chapter, it proposes a focus on the main subsystems that make a zero-emission vehicle (ZEV), examining current features and topological configurations proposed in the literature. This analysis is preliminary to the various electric vehicle architectures proposed in the final paragraph. In particular, the electric drive represents the core of the electric vehicle propulsion. It is realized by different subsystems that have a single mission: ensure the requested power/energy based on the operating condition. Particular attention will be devoted to power subsystems, which are the fundamental elements to improving the performance of the ZEV.

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Section: Charging Interfacementioning

confidence: 99%

Overview of Main Electric Subsystems of Zero-Emission Vehicles

Dannier¹

2019

Propulsion Systems

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“…For station operators, buffer batteries offer additional benefits such as lowering the power connection requirements and relaxing the constraints on the grid. Tsirinomeny [8] estimated a typical battery for a station serving 200 BEVs/day to have a capacity of 2.2 MWh and a maximum power output of 1.6 MW (32 chargers at 50 kW with a peak grid demand of 400 kW).…”

Section: Battery Electric Vehicle Infrastructurementioning

confidence: 99%

“…Several technologies are available, and we can mention, for example, flow batteries (e.g., all vanadium or zinc bromine), lithium-ion, lithium polymer and lithium titanate. Introducing mega batteries in stations with multiple fast chargers has several benefits such as peak shaving, load leveling and buffering, as well as relaxing the constraints for grid connection [4,8,25]. A real implementation of a DC fast charging station coupled with a battery storage system was performed by Sbordone et al [26] with a peak shaving strategy.…”

Section: Stationary Storagementioning

confidence: 99%

Mobility from Renewable Electricity: Infrastructure Comparison for Battery and Hydrogen Fuel Cell Vehicles

Ligen

Vrubel

Girault

2018

WEVJ

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This work presents a detailed breakdown of the energy conversion chains from intermittent electricity to a vehicle, considering battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). The traditional well-to-wheel analysis is adapted to a grid to mobility approach by introducing the intermediate steps of useful electricity, energy carrier and on-board storage. Specific attention is given to an effective coupling with renewable electricity sources and associated storage needs. Actual market data show that, compared to FCEVs, BEVs and their infrastructure are twice as efficient in the conversion of renewable electricity to a mobility service. A much larger difference between BEVs and FCEVs is usually reported in the literature. Focusing on recharging events, this work additionally shows that the infrastructure efficiencies of both electric vehicle (EV) types are very close, with 57% from grid to on-board storage for hydrogen refilling stations and 66% for fast chargers coupled with battery storage. The transfer from the energy carrier at the station to on-board storage in the vehicle accounts for 9% and 12% of the total energy losses of these two modes, respectively. Slow charging modes can achieve a charging infrastructure efficiency of 78% with residential energy storage systems coupled with AC chargers.

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“…Many studies assume demand will be proportional to traffic flow measurements [15], [16] or F o r P e e r R e v i e w "mobility" measurements for urban areas [17]. These prediction methods give a characteristic two peak EV demand profile, with EVs more likely to visit an HREVC in the morning and the evening, aligning with the high use times for the road network.…”

Section: A Backgroundmentioning

confidence: 99%

A Stochastic Method for Prediction of the Power Demand at High Rate EV Chargers

Hilton

Kiaee

Bryden

et al. 2018

IEEE Trans. Transp. Electrific.

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High rate (<100kW) electric vehicle chargers (HREVCs) are crucial for achieving the benefits of reduced CO 2 and particulate emissions promised by electric vehicles by enabling journey distances greater than the range of the vehicle. A method for predicting the expected demand pattern at these HREVCs is presented in this paper. This is critical to planning a network of chargers. This novel method uses freely available traffic flow data and travel patterns extracted from the open street map combined with a novel EV battery capacity prediction method, to find future HREVC usage patterns in the UK and their dependence on location and EV characteristics. This planning method can be replicated to find HREVC power demand for any location on the strategic road network in the UK and can be used in analysis of the role of high rate EV charging in the wider energy system. Index Terms Vehicles, Battery chargers, Power system modeling, Load modeling I. INTRODUCTION The use of fossil fuel vehicles contributes to climate change through the release of CO 2 , nitrous oxides and unburnt hydrocarbons, and causes harmful levels of pollution to be present in cities around the world [1]. The removal of fossil fuels from the transport industry is therefore of clear importance. One method to achieve this which is currently gaining traction is the introduction of electric vehicles (EVs). EVs have the advantage of zero local gaseous emissions and improved

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Optimizing EV driving-recharge time ratio a under limited grid connection

Cited by 7 publications

References 6 publications

Overview of Main Electric Subsystems of Zero-Emission Vehicles

Overview of Main Electric Subsystems of Zero-Emission Vehicles

Mobility from Renewable Electricity: Infrastructure Comparison for Battery and Hydrogen Fuel Cell Vehicles

A Stochastic Method for Prediction of the Power Demand at High Rate EV Chargers

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