Aging behavior of an electric vehicle battery system considering real drive conditions

[Display omitted] •Modeling EV’s powertrain, battery pack TMS, detailed cabin, and HVAC systems.•Assessments of EV performance under annual dynamic environmental conditions.•Using vehicle-based dynamic temperature and power profiles for aging calculation.•Battery aging calculation for 10 years, incl...

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Veröffentlicht in:Energy conversion and management 2024-03, Vol.304, p.118213, Article 118213
Hauptverfasser: Bamdezh, M.A., Molaeimanesh, G.R.
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Sprache:eng
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Zusammenfassung:[Display omitted] •Modeling EV’s powertrain, battery pack TMS, detailed cabin, and HVAC systems.•Assessments of EV performance under annual dynamic environmental conditions.•Using vehicle-based dynamic temperature and power profiles for aging calculation.•Battery aging calculation for 10 years, including 22 working days for each month.•At the end of the 10th year the total capacity loss of the battery is 7.1%. In this article, a comprehensive study of the aging behavior of an electric vehicle battery pack considering the vehicle's operation under real driving conditions, such as ambient temperature, humidity, and solar irradiation conditions, in all different months of the year for a 10-year time horizon with two different working scenarios is investigated for the first time. The vehicle duty cycle represents a personal vehicle traveling once at 7:00 AM from home to work and returning at 5:00 PM from work to home for scenario 1. For the second scenario, 8:30 AM is set for outbound trips, and 6:30 PM is set for return trips via the WLTP driving cycle. The target temperature for the cabin and battery pack are set to 22 °C and 28 °C, respectively. The results indicate the highest energy consumption is for the cold season. The EV's energy consumptions in scenario 2 for outbound and return trips were 20 % less and 0.6 % more than the EV's energy consumptions in scenario 1 for outbound and return trips, respectively. Next, the battery aging was evaluated for ten years, resulting in 7.16 % and 6.99 % total capacity loss for scenario 1 and scenario 2, respectively.
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2024.118213