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Other research product . Other ORP type . 2020

Which combination of battery capacity and charging power for battery electric vehicles: urban versus rural French case studies

HAIDAR, Bassem; Da Costa, Pascal; Lepoutre, Jan; Vidal, Fabrice;
Published: 25 Nov 2020
Publisher: HAL CCSD
Country: France
FAEE SEMINAR; Battery Electric Vehicles (BEVs) are essential for reducing greenhouse gas emissions related to the transport sector towards meeting global emissions targets. Although this technology is gaining much attention, techno-economic barriers hinder the widespread of BEVs, namely the high investments, the limited autonomy, and the lack of public-charging infrastructure. A bigger battery leads simultaneously to more autonomy and higher-priced BEV, due to the battery-pack cost. Deploying more public chargers, a solution for limited autonomy BEVs, is facing other obstacles: vehicle-charger adaptability in terms of charging power, and additional investments for charging operators. Therefore, this paper aims to find the most cost-efficient solution(s) of battery capacity and charging power combination(s), considering technoeconomic factors. Based on French travel surveys data, we simulate the needs of 12 scenarios of 5,000 identical privately-purchased BEVs, by changing their battery capacity for both urban and rural areas, before determining the optimal number of charging stations. We then analyze the BEV owner and the charging operator business models in order to conclude with win-win situations for both parties. Results show cheaper investments in charging infrastructure, especially 22 kW charger, rather than in bigger batteries. For urban (rural) areas, purchasing a 35 to 50 kWh BEV (65 kWh BEV for rural) and deploying 22 and 50 kW chargers (50 kW for rural) proves the most cost-efficient and profitable solutions for both BEV owners and charging operators. We finally recommend charging operators to review their charging tariffs, and to take into account the acceptability of customer.

Battery range, Charging infrastructure, Electric vehicles, Innovative business model, Techno-economic scenarios, [QFIN]Quantitative Finance [q-fin], [SPI]Engineering Sciences [physics]

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ACEA, 2019. ACEA Report Vehicles in use-Europe 2019 [WWW Document]. URL (accessed 10.13.20).

Advenir, project, 2020. ADVENIR ∣ Primes CEE pour points de recharge des véhicules électriques [WWW Document]. ADVENIR. URL (accessed 10.26.20).

Alhazmi, Y.A., Mostafa, H.A., Salama, M.M.A., 2017. Optimal allocation for electric vehicle charging stations using Trip Success Ratio. Int. J. Electr. Power Energy Syst. 91, 101- 116.

Alizécharge, 2020. Alizé Charge - Bornes de recharge pour voitures électriques [WWW Document]. URL (accessed 10.27.20).

Amjad, M., Ahmad, A., Rehmani, M.H., Umer, T., 2018. A review of EVs charging: From the perspective of energy optimization, optimization approaches, and charging techniques. Transp. Res. Part Transp. Environ. 62, 386-417.

Bhat, U.N., 2015. An Introduction to Queueing Theory: Modeling and Analysis in Applications, 2nd ed, Statistics for Industry and Technology. Birkhäuser Basel.