Electric Vehicle Battery Cycle Aging Evaluation in Real-World Daily Driving and Vehicle-to-Grid Services
Abstract
In this paper, battery lifetime estimation of an electric vehicle (EV) using different driving styles on arterial roads integrating recharging scenarios in the neighborhood of the vehicle-to-grid integration is studied. The real-world driving cycles from a fleet of connected vehicles are evaluated in an EV model with different charging options. Daily utility services are added to the simulations to explore the whole day performance of the battery and its daily degradation. Fifty driving cycles from different drivers on arterial roads are classified into aggressive, mild, and gentle drivers based on their driving acceleration behavior. The standard levels 1 and 2 chargers are considered for recharging and the frequency regulation, and peak shaving and solar energy storage are assumed for the daily ancillary services. The results indicate that the aggressive driving and recharging behavior have significant effect on the battery life reduction. In addition, the daily utility services impose extra degradation of the battery. Also, the effect of temperature change on the battery degradation is explored. Simulation of active versus passive thermal management systems in three different climates shows the significant impact of the battery temperature on its capacity fade.
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Research shows that daily 2-hour frequency regulation would consume the battery capacity by 14.3%, and adding peak shaving would take up to 35.6%.
“Research shows that daily 2-hour frequency regulation would consume the battery capacity by 14.3%, and adding peak shaving would take up to 35.6% [42].”
From A Review of Bidirectional On-Board Chargers for Electric Vehicles (2021) · cites this paper as [42]
The V2G mode can balance the load by shaving peak and filling valley according to the grid demand.
“For example, it can balance the load by shaving peak and lling valley according to the grid demand [42].”
From A Review of Bidirectional On-Board Chargers for Electric Vehicles (2021) · cites this paper as [42]
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- Authors
- Jafari, M., Gauchia, A., Zhao, S., Zhang, K., & Gauchia, L.
- Affiliations
- Michigan Technological University (US)
- Venue
- IEEE Transactions on Transportation Electrification
- Published
- 2018-03
- Volume
- 4
- Issue
- 1
- Pages
- 122-134
- ISSN
- 2332-7782 (ISSN-L)
- OpenAlex
- W2765498684
- Cited by
- 177
- References
- 39
- Citations by year
- 2026: 18 · 2025: 19 · 2024: 26 · 2023: 19 · 2022: 31 · 2021: 27 · 2020: 16 · 2019: 12 · 2018: 8 · 2017: 1
- FWCI
- 6.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Transportation Electrification (publishedVersion)
- Digital Commons - Michigan Tech (Michigan Technological University) (submittedVersion)
- Funders
- National Science Foundation through the project CAREER: An Ecologically Inspired Approach to Battery Lifetime Analysis and Testing (1651256)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Keywords
- battery lifetime prediction, driving style, aggressive driving, real-world driving cycles, vehicle-to-grid, frequency regulation, peak shaving, solar energy storage, battery charging, capacity fade, battery temperature, thermal management, passive thermal management, active thermal control
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