Estimate long-term impact on battery degradation by considering electric vehicle real-world end-use factors

电池(电) 汽车工程 航程(航空) 担保 泄流深度 电动汽车 电动汽车 电池容量 降级(电信) 模拟 计算机科学 工程类 环境科学 电气工程 法学 功率(物理) 航空航天工程 物理 量子力学 政治学
作者
Shiqi Ou
出处
期刊:Journal of Power Sources [Elsevier]
卷期号:573: 233133-233133 被引量:36
标识
DOI:10.1016/j.jpowsour.2023.233133
摘要

Many estimates of battery capacity degradation are based on accelerated lab tests that involve charge-discharge cycles or rely on data or electrochemical modeling. These methods are reasonable for technology benchmarking but rarely consider real-world end-use factors. To address this issue, this study develops the Battery Run-down under Electric Vehicle Operation (BREVO) model. It links the driver's travel pattern to physics-based battery degradation and powertrain energy consumption models. The model simulates the impacts of charging behavior, charging rate, driving patterns, and multiple energy management modules on battery capacity degradation. It finds that, over a 10-year timespan, firstly, for a random driver situated in the New England area, daily direct-current fast charging (60 kW) could lead to up to 22% less battery capacity when compared to daily Level-1 charging (1.8 kW). Second, the battery thermal management system can delay battery degradation by approximately 0.5% in the New England area. Third, warmer ambient temperatures enhance BEV battery usage. The model indicates that the battery capacity in the Los Angeles area is 6% higher than that in the New England area. The BREVO model provides crucial information for consumers and BEV manufacturers on range anxiety, BEV battery design, and decision support of battery warranty.
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